期刊
JOURNAL OF CLIMATE
卷 32, 期 14, 页码 4409-4430出版社
AMER METEOROLOGICAL SOC
DOI: 10.1175/JCLI-D-18-0789.1
关键词
Atmosphere; Precipitation; Cloud microphysics; Climate models; Aerosol indirect effect; Aerosol-cloud interaction
资金
- NOAA's Climate Program Office's Modeling, Analysis, Predictions and Projections program [NA15OAR4310153]
- Integrated Research Program for Advancing Climate Models (TOUGOU program) from the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan
- JAXA EarthCARE project
- JAXA GCOM-C project
Global climate models (GCMs) have been found to share the common too-frequent bias in the warm rain formation process. In this study, five different autoconversion schemes are incorporated into a single GCM, to systematically evaluate the warm rain formation processes in comparison with satellite observations and investigate their effects on the aerosol indirect effect (AIE). It is found that some schemes generate warm rain less efficiently under polluted conditions in the manner closer to satellite observations, while the others generate warm rain too frequently. Large differences in AIE are found among these schemes. It is remarkable that the schemes with more observation-like warm rain formation processes exhibit larger AIEs that far exceed the uncertainty range reported in IPCC AR5, to an extent that can cancel much of the warming trend in the past century, whereas schemes with too-frequent rain formations yield AIEs that are well bounded by the reported range. The power-law dependence of the autoconversion rate on the cloud droplet number concentration beta is found to affect substantially the susceptibility of rain formation to aerosols: the more negative beta is, the more difficult it is for rain to be triggered in polluted clouds, leading to larger AIE through substantial contributions from the wet scavenging feedback. The appropriate use of a droplet size threshold can mitigate the effect of a less negative beta. The role of the warm rain formation process on AIE in this particular model has broad implications for others that share the too-frequent rain-formation bias.
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