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An observational radiative constraint on hydrologic cycle intensification

Author

Listed:
  • Anthony M. DeAngelis

    (University of California Los Angeles)

  • Xin Qu

    (University of California Los Angeles)

  • Mark D. Zelinka

    (Program for Climate Model Diagnosis and Intercomparison, Lawrence Livermore National Laboratory)

  • Alex Hall

    (University of California Los Angeles)

Abstract

The magnitude of global precipitation increase predicted by climate models has a large uncertainty that has been difficult to constrain, but much of the range in predictions is now shown to arise from shortcomings in the modelling of atmospheric absorption of shortwave radiation; if the radiative transfer algorithms controlling the absorption were more accurate, the model spread would narrow and the mean estimate could be about 40% lower.

Suggested Citation

  • Anthony M. DeAngelis & Xin Qu & Mark D. Zelinka & Alex Hall, 2015. "An observational radiative constraint on hydrologic cycle intensification," Nature, Nature, vol. 528(7581), pages 249-253, December.
    • Handle: RePEc:nat:nature:v:528:y:2015:i:7581:d:10.1038_nature15770
    DOI: 10.1038/nature15770
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    Cited by:

    1. Wenyu Zhou & L. Ruby Leung & Nicholas Siler & Jian Lu, 2023. "Future precipitation increase constrained by climatological pattern of cloud effect," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    2. Wenxia Zhang & Kalli Furtado & Tianjun Zhou & Peili Wu & Xiaolong Chen, 2022. "Constraining extreme precipitation projections using past precipitation variability," Nature Communications, Nature, vol. 13(1), pages 1-11, December.

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