Impacts of Precipitation Modeling on Cloud Feedback in MIROC6. Issue 5 (4th March 2022)

• Record Type: Journal Article
• Authors: Hirota, N.; Michibata, T.; Shiogama, H.; Ogura, T.; Suzuki, K.
• Is Part Of: Geophysical research letters. Volume 49:Issue 5(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-03-04
• Subjects: Geophysics -- Periodicals; Planets -- Periodicals; Lunar geology -- Periodicals; 550
• DOI: 10.1029/2021GL096523
• Languages: English
• ISSNs: 0094-8276

Abstract

Abstract: Uncertainties in cloud feedback remain stubbornly significant in global climate models, disrupting the credibility of climate projections. This study examined the impacts of the prognostic treatment of precipitation on cloud feedback using the Model for Interdisciplinary Research on Climate version 6 (MIROC6). In a prognostic precipitation scheme, precipitating hydrometers are explicitly predicted, allowing a more sophisticated representation of their microphysical and radiative effects than that of traditional diagnostic schemes. The introduction of the prognostic scheme in MIROC6 increases cloud feedback associated with the elevated altitude of clouds in warming climates. Moreover, the equilibrium climate sensitivity increases by about 20%. Because associated high‐level clouds are better represented in the prognostic scheme, climate projections with larger altitude feedback are considered more credible. Additional analyses of Coupled Model Intercomparison Project models suggests that their altitude cloud feedback would be higher if their underestimation of high‐level clouds were mitigated. Plain Language Summary: Uncertainties in global mean temperature projections are primarily associated with the spread in cloud feedback across models, which accelerate or decelerate global warming through cloud sunshade and/or greenhouse effects. A possible reason for the spread in cloud response is the overly simplified treatment of precipitation in models, where rain and snow particles immediately fall from the atmosphere down to the surface within a single model time interval of about 10 min. Here, we introduced a more sophisticated precipitation scheme that explicitly calculates the physical processes of falling rain and snow particles, thus preserving their "memory" in the atmosphere with their sunshade and greenhouse effects incorporated. As a result, the representation of clouds is significantly improved in this model, and greenhouse effects by clouds in warming climates are significantly enhanced. This study lends credence to higher cloud feedback and climate sensitivity if models incorporate the missing feedback processes in line with observational constraints. Key Points: Acceleration of global warming by cloud altitude feedback is enhanced in MIROC6 when a prognostic precipitation scheme is introduced Cloud altitude feedback is associated with high clouds in the present climate, which is better represented by prognostic precipitation Cloud altitude feedback in CMIP models is suggested to increase when their underestimation of high‐level clouds is mitigated