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An Energy-Balance Analysis of Deep Convective Self-Aggregation above Uniform SST
Open accessAbstract
The spatial organization of deep moist convection in radiative–convective equilibrium over a constant sea surface temperature is studied. A 100-day simulation is performed with a three-dimensional cloud-resolving model over a (576 km)2 domain with no ambient rotation and no mean wind. The convection self-aggregates within 10 days into quasi-stationary mesoscale patches of dry, subsiding and moist, rainy air columns. The patches ultimately merge into a single intensely convecting moist patch surrounded by a broad region of very dry subsiding air. The self-aggregation is analyzed as an instability of a horizontally homogeneous convecting atmosphere driven by convection–water vapor–radiation feedbacks that systematically dry the drier air columns and moisten the moister air columns. Column-integrated heat, water, and moist static energy budgets over (72 km)2 horizontal blocks show that this instability is primarily initiated by the reduced radiative cooling of air columns in which there is extensive anvil cirrus, augmented by enhanced surface latent and sensible heat fluxes under convectively active regions due to storm-induced gustiness. Mesoscale circulations intensify the later stages of self-aggregation by fluxing moist static energy from the dry to the moist regions. A simple mathematical model of the initial phase of self-aggregation is proposed based on the simulations. In accordance with this model, the self-aggregation can be suppressed by horizontally homogenizing the radiative cooling or surface fluxes. Lower-tropospheric wind shear leads to slightly slower and less pronounced self-aggregation into bands aligned along the shear vector. Self-aggregation is sensitive to the ice microphysical parameterization, which affects the location and extent of cirrus clouds and their radiative forcing. Self-aggregation is also sensitive to ambient Coriolis parameter f, and can induce spontaneous tropical cyclogenesis for large f. Inclusion of an interactive mixed-layer ocean slows but does not prevent self-aggregation.
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Cited by
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Sherwood, S. C., Webb, M. J., Annan, J. D., Armour, K. C., Forster, P. M., Hargreaves, J. C., Hegerl, G., Klein, S. A., Marvel, K. D., Rohling, E. J., et al. (2020) · Reviews of Geophysics · doi:10.1029/2019rg000678 · Cited by 1,254
Self-citationCloud feedback mechanisms and their representation in global climate models
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Entrainment and detrainment in cumulus convection: an overview
de Rooy, W. C., Bechtold, P., Fröhlich, K., Hohenegger, C., Jonker, H., Mironov, D., Pier Siebesma, A., Teixeira, J., & Yano, J. (2013) · Quarterly Journal of the Royal Meteorological Society · doi:10.1002/qj.1959 · Cited by 384
Thermodynamic control of anvil cloud amount
Bony, S., Stevens, B., Coppin, D., Becker, T., Reed, K. A., Voigt, A., & Medeiros, B. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1601472113 · Cited by 299
An Idealized Semi-Empirical Framework for Modeling the Madden–Julian Oscillation
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Metadata
- Authors
- Bretherton, C. S., Blossey, P. N., & Khairoutdinov, M.
- Venue
- Journal of the Atmospheric Sciences
- Publisher
- American Meteorological Society
- Published
- 2005-12-01
- Volume
- 62
- Issue
- 12
- Pages
- 4273-4292
- ISSN
- 0022-4928 (ISSN-L)
- 1520-0469
- OpenAlex
- W2161103622
- Cited by
- 557
- References
- 0
- FWCI
- 4.05
- Type
- journal article
- Language
- en
- Open access
- bronze
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