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Prognostic Precipitation in the MIROC6-SPRINTARS GCM: Description and Evaluation Against Satellite Observations

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  • Journal Title:
    Journal of Advances in Modeling Earth Systems
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  • Description:
    A comprehensive two-moment microphysics scheme is incorporated into the MIROC6-SPRINTARS general circulation model (GCM). The new scheme includes prognostic precipitation for both rain and snow and considers their radiative effects. To evaluate the impacts of applying different treatments of precipitation and the associated radiative effect, we perform climate simulations employing both the traditional diagnostic and new prognostic precipitation schemes, the latter also being tested with and without incorporating the radiative effect of snow. The prognostic precipitation, which maintains precipitation in the atmosphere across multiple time steps, models the ratio of accretion to autoconversion as being approximately an order of magnitude higher than that for the diagnostic scheme. Such changes in microphysical process rates tend to reduce the cloud water susceptibility as the autoconversion process is the only pathway through which aerosols can influence rain formation. The resultant anthropogenic aerosol effect is reduced by approximately 21% in the prognostic precipitation scheme. Modifications to the microphysical process rates also change the vertical distribution of hydrometeors in the manner that increases the fractional occurrence of single-layered warm clouds by 38%. The new scheme mitigates the excess of supercooled liquid water produced by the previous scheme and increases the total mass of ice hydrometeors. Both characteristics are consistent with CloudSat/CALIPSO retrievals. The radiative effect of snow is significant at both longwave and shortwave (6.4 and 5.1 W/m(2) in absolute values, respectively) and can alter the precipitation fields via energetic controls on precipitation. These results suggest that the prognostic precipitation scheme, with its radiative effects incorporated, makes an indispensable contribution to improving the reliability of climate modeling.
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  • Source:
    Journal of Advances in Modeling Earth Systems 11(3), 839-860, 2019
  • DOI:
  • Document Type:
    Journal Article
  • Funding:
    Grant no. NA15OAR4310153
  • Rights Information:
    CC BY-NC-ND
  • Compliance:
    PMC
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