The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Intercomparison of the cloud water phase among global climate models: CLOUD WATER PHASE IN GCMs
Open accessAbstract
Mixed-phase clouds (clouds that consist of both cloud droplets and ice crystals) are frequently present in the Earth's atmosphere and influence the Earth's energy budget through their radiative properties, which are highly dependent on the cloud water phase. In this study, the phase partitioning of cloud water is compared among six global climate models (GCMs) and with Cloud and Aerosol Lidar with Orthogonal Polarization retrievals. It is found that the GCMs predict vastly different distributions of cloud phase for a given temperature, and none of them are capable of reproducing the spatial distribution or magnitude of the observed phase partitioning. While some GCMs produced liquid water paths comparable to satellite observations, they all failed to preserve sufficient liquid water at mixed-phase cloud temperatures. Our results suggest that validating GCMs using only the vertically integrated water contents could lead to amplified differences in cloud radiative feedback. The sensitivity of the simulated cloud phase in GCMs to the choice of heterogeneous ice nucleation parameterization is also investigated. The response to a change in ice nucleation is quite different for each GCM, and the implementation of the same ice nucleation parameterization in all models does not reduce the spread in simulated phase among GCMs. The results suggest that processes subsequent to ice nucleation are at least as important in determining phase and should be the focus of future studies aimed at understanding and reducing differences among the models.
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Cites
Lamarque, J.-F., Bond, T. C., Eyring, V., Granier, C., Heil, A., Klimont, Z., Lee, D., Liousse, C., Mieville, A., Owen, B., et al. (2010) · Atmospheric Chemistry and Physics · doi:10.5194/acp-10-7017-2010 · Cited by 2,105
Cited by
Observational constraints on mixed-phase clouds imply higher climate sensitivity
Tan, I., Storelvmo, T., & Zelinka, M. D. (2016) · Science · doi:10.1126/science.aad5300 · Cited by 527
Self-citationCloud feedback mechanisms and their representation in global climate models
Ceppi, P., Brient, F., Zelinka, M. D., & Hartmann, D. L. (2017) · WIREs Climate Change · doi:10.1002/wcc.465 · Cited by 430
Mixed-Phase Clouds: Progress and Challenges
Korolev, A., McFarquhar, G., Field, P. R., Franklin, C., Lawson, P., Wang, Z., Williams, E., Abel, S. J., Axisa, D., Borrmann, S., et al. (2017) · Meteorological Monographs · doi:10.1175/amsmonographs-d-17-0001.1 · Cited by 455
Self-citationThe role of cloud phase in Earth's radiation budget
Matus, A. V., & L'Ecuyer, T. S. (2017) · Journal of Geophysical Research: Atmospheres · doi:10.1002/2016jd025951 · Cited by 359
Feinberg, A., Sukhodolov, T., Luo, B.-P., Rozanov, E., Winkel, L. H. E., Peter, T., & Stenke, A. (2019) · Geoscientific Model Development · doi:10.5194/gmd-12-3863-2019 · Cited by 84
Metadata
- Authors
- Komurcu, M., Storelvmo, T., Tan, I., Lohmann, U., Yun, Y., Penner, J. E., Wang, Y., Liu, X., & Takemura, T.
- Venue
- Journal of Geophysical Research: Atmospheres
- Publisher
- American Geophysical Union (AGU)
- Published
- 2014-03-27
- Volume
- 119
- Issue
- 6
- Pages
- 3372-3400
- ISSN
- 0148-0227 (ISSN-L)
- 2169-897X
- OpenAlex
- W1596195367
- Cited by
- 200
- References
- 1
- FWCI
- 12.48
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Komurcu, M., Storelvmo, T., Tan, I., Lohmann, U., Yun, Y., Penner, J. E., Wang, Y., Liu, X., & Takemura, T. (2014). Intercomparison of the cloud water phase among global climate models: CLOUD WATER PHASE IN GCMs. Journal of Geophysical Research: Atmospheres. https://doi.org/10.1002/2013jd021119
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