Journal cover Journal topic
Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
Atmos. Chem. Phys., 16, 15413-15424, 2016
http://www.atmos-chem-phys.net/16/15413/2016/
doi:10.5194/acp-16-15413-2016
© Author(s) 2016. This work is distributed
under the Creative Commons Attribution 3.0 License.
Research article
13 Dec 2016
The source of discrepancies in aerosol–cloud–precipitation interactions between GCM and A-Train retrievals
Takuro Michibata1,2, Kentaroh Suzuki3, Yousuke Sato4, and Toshihiko Takemura2 1Department of Earth System Science and Technology, Kyushu University, Fukuoka, Japan
2Research Institute for Applied Mechanics, Kyushu University, Fukuoka, Japan
3Atmosphere and Ocean Research Institute, The University of Tokyo, Chiba, Japan
4RIKEN Advanced Institute for Computational Science, Hyogo, Japan
Abstract. Aerosol–cloud interactions are one of the most uncertain processes in climate models due to their nonlinear complexity. A key complexity arises from the possibility that clouds can respond to perturbed aerosols in two opposite ways, as characterized by the traditional “cloud lifetime” hypothesis and more recent “buffered system” hypothesis. Their importance in climate simulations remains poorly understood. Here we investigate the response of the liquid water path (LWP) to aerosol perturbations for warm clouds from the perspective of general circulation model (GCM) and A-Train remote sensing, through process-oriented model evaluations. A systematic difference is found in the LWP response between the model results and observations. The model results indicate a near-global uniform increase of LWP with increasing aerosol loading, while the sign of the response of the LWP from the A-Train varies from region to region. The satellite-observed response of the LWP is closely related to meteorological and/or macrophysical factors, in addition to the microphysics. The model does not reproduce this variability of cloud susceptibility (i.e., sensitivity of LWP to perturbed aerosols) because the parameterization of the autoconversion process assumes only suppression of rain formation in response to increased cloud droplet number, and does not consider macrophysical aspects that serve as a mechanism for the negative responses of the LWP via enhancements of evaporation and precipitation. Model biases are also found in the precipitation microphysics, which suggests that the model generates rainwater readily even when little cloud water is present. This essentially causes projections of unrealistically frequent and light rain, with high cloud susceptibilities to aerosol perturbations.

Citation: Michibata, T., Suzuki, K., Sato, Y., and Takemura, T.: The source of discrepancies in aerosol–cloud–precipitation interactions between GCM and A-Train retrievals, Atmos. Chem. Phys., 16, 15413-15424, doi:10.5194/acp-16-15413-2016, 2016.
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Short summary
This study identifies a fundamental flaw of a GCM in aerosol–cloud–precipitation interactions. The model predicts a monotonic increase in the LWP in response to increased aerosols, which is in stark contrast to satellite retrievals that show a regional variation in the sign of the LWP response. The model also fails to represent the observed dependency of the LWP response on macrophysical regimes. The model biases are attributed to the autoconversion process, with a lack of buffering mechanisms.
This study identifies a fundamental flaw of a GCM in aerosol–cloud–precipitation...
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