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Aerosol effects on cloud water amounts were successfully simulated by a global cloud-system resolving model

Author

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  • Yousuke Sato

    (Nagoya University
    RIKEN Advanced Institute for Computational Science, 7-1-26, Minatojima-minami-machi, Chuo-ku, Kobe)

  • Daisuke Goto

    (National Institute for Environmental Studies)

  • Takuro Michibata

    (Kyushu University)

  • Kentaroh Suzuki

    (The University of Tokyo)

  • Toshihiko Takemura

    (Kyushu University)

  • Hirofumi Tomita

    (RIKEN Advanced Institute for Computational Science, 7-1-26, Minatojima-minami-machi, Chuo-ku, Kobe)

  • Teruyuki Nakajima

    (Earth Observation Research Center, Japan Aerospace Exploration Agency, 2-1-1, Sengen, Tsukuba)

Abstract

Aerosols affect climate by modifying cloud properties through their role as cloud condensation nuclei or ice nuclei, called aerosol–cloud interactions. In most global climate models (GCMs), the aerosol–cloud interactions are represented by empirical parameterisations, in which the mass of cloud liquid water (LWP) is assumed to increase monotonically with increasing aerosol loading. Recent satellite observations, however, have yielded contradictory results: LWP can decrease with increasing aerosol loading. This difference implies that GCMs overestimate the aerosol effect, but the reasons for the difference are not obvious. Here, we reproduce satellite-observed LWP responses using a global simulation with explicit representations of cloud microphysics, instead of the parameterisations. Our analyses reveal that the decrease in LWP originates from the response of evaporation and condensation processes to aerosol perturbations, which are not represented in GCMs. The explicit representation of cloud microphysics in global scale modelling reduces the uncertainty of climate prediction.

Suggested Citation

  • Yousuke Sato & Daisuke Goto & Takuro Michibata & Kentaroh Suzuki & Toshihiko Takemura & Hirofumi Tomita & Teruyuki Nakajima, 2018. "Aerosol effects on cloud water amounts were successfully simulated by a global cloud-system resolving model," Nature Communications, Nature, vol. 9(1), pages 1-7, December.
    • Handle: RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-018-03379-6
    DOI: 10.1038/s41467-018-03379-6
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