Size Distributions and Dynamical Properties of Shallow Cumulus Clouds from Aircraft Observations and Satellite Data

Rodts, S. M. A.; Duynkerke, Peter G.; Jonker, Harm J. J.

doi:10.1175/1520-0469(2003)060<1895:sdadpo>2.0.co;2

Cited by 96 publications

(127 citation statements)

References 38 publications

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“…The cloud core, with positive vertical velocity and buoyancy, is surrounded by a descending shell with negative buoyancy and finally an outer shell representing the ambient dry air. The descending shell forms as a result of evaporative cooling (Turner, 1966) and has been observed in reality (Jonas, 1990;Rodts et al, 2003; as well as in LES . argue that lateral entrainment can be reconciled with observations showing that entrained air appears to originate at higher levels by noting that any laterally entrained dry air must be entrained via the descending shell.…”

Section: Entrainment In Cumulus Cloudsmentioning

confidence: 83%

Droplet growth in warm turbulent clouds

Devenish

Bartello

Brenguier

et al. 2012

Quart J Royal Meteoro Soc

243

281

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In this survey we consider the impact of turbulence on cloud formation from the cloud scale to the droplet scale. We assess progress in understanding the effect of turbulence on the condensational and collisional growth of droplets and the effect of entrainment and mixing on the droplet spectrum. The increasing power of computers and better experimental and observational techniques allow for a much more detailed study of these processes than was hitherto possible. However, much of the research necessarily remains idealized and we argue that it is those studies which include such fundamental characteristics of clouds as droplet sedimentation and latent heating that are most relevant to clouds. Nevertheless, the large body of research over the last decade is beginning to allow tentative conclusions to be made. For example, it is unlikely that small-scale turbulent eddies (i.e. not the energy-containing eddies) alone are responsible for broadening the droplet size spectrum during the initial stage of droplet growth due to condensation. It is likely, though, that small-scale turbulence plays a significant role in the growth of droplets through collisions and coalescence. Moreover, it has been possible through detailed numerical simulations to assess the relative importance of different processes to the turbulent collision kernel and how this varies in the parameter space that is important to clouds. The focus of research on the role of turbulence in condensational and collisional growth has tended to ignore the effect of entrainment and mixing and it is arguable that they play at least as important a role in the evolution of the droplet spectrum. We consider the role of turbulence in the mixing of dry and cloudy air, methods of quantifying this mixing and the effect that it has on the droplet spectrum. Copyright

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Section: Entrainment In Cumulus Cloudsmentioning

confidence: 83%

Droplet growth in warm turbulent clouds

Devenish

Bartello

Brenguier

et al. 2012

Quart J Royal Meteoro Soc

243

281

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“…Observational evidence (e.g. Jonas, 1990;Rodts et al, 2003) as well as an LES study reveal the existence of a descending shell with properties significantly different from the average environment (section 3.8).…”

Section: Conclusion and Discussionmentioning

confidence: 96%

“…Observational studies by, for example, Jonas (1990), Rodts et al (2003) and more recently by Wang et al (2009) and Heus et al (2009a), reveal how the (thermo)dynamic and microphysical properties of the near-cloud environment differ significantly from the environmental properties further away from the cloud. Studying individual cloud transects, Jonas (1990) noted the presence of a thin shell of subsiding air surrounding clouds and pointed out the importance of it for understanding the droplet spectrum in clouds, taking into account that the shell in principle could contain air with cloud-top properties.…”

Section: Relevance Of the Near Vicinity Of Cloudsmentioning

confidence: 99%

“…As to the cause of the descending shell, Jonas (1990) identified two mechanisms, mechanical forcing and evaporative cooling resulting from mixing saturated and unsaturated air at the cloud edge. As a follow-up, Rodts et al (2003) studied a large number of horizontal cloud transects measured during the Small Cumulus Microphysics Study (SCMS; Knight and Miller, 1998), and created a statistical average by normalizing each transect by the corresponding cloud width. They confirmed the persistent occurrence of the descending shell of air surrounding the cloud and found their data to be most consistent with the mechanism of evaporative cooling.…”

Section: Relevance Of the Near Vicinity Of Cloudsmentioning

confidence: 99%

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Entrainment and detrainment in cumulus convection: an overview

Rooy

Bechtold

Fröhlich

et al. 2012

Quart J Royal Meteoro Soc

293

256

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Entrainment and detrainment processes have been recognised for a long time as key processes for cumulus convection and have recently witnessed a regrowth of interest mainly due to the capability of large-eddy simulations (LES) to diagnose these processes in more detail. This article has a twofold purpose. Firstly, it provides a historical overview of the past research on these mixing processes, and secondly, it highlights more recent important developments. These include both fundamental process studies using LES aiming to improve our understanding of the mixing process, but also more practical studies targeted toward an improved parametrised representation of entrainment and detrainment in large-scale models. A highlight of the fundamental studies resolves a long-lasting controversy by showing that lateral entrainment is the dominant mixing mechanism in comparison with the cloud-top entrainment in shallow cumulus convection. The more practical studies provide a wide variety of new parametrisations with sometimes conflicting approaches to the way in which the effect of the free tropospheric humidity on the lateral mixing is taken into account. An important new insight that will be highlighted is that, despite the focus in the literature on entrainment, it appears that it is rather the detrainment process that determines the vertical structure of the convection in general and the mass flux especially. Finally, in order to speed up progress and stimulate convergence in future parametrisations, stronger and more systematic use of LES is advocated.

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“…Measuring vertical velocities in the atmosphere is difficult, mostly because of their relatively small magnitude. In-situ measurements are, in practice, only possible with research aircraft (Duynkerke et al, 1999;Rodts et al, 2003;Snider et al, 2003;Guo et al, 2008;Lu et al, 2009;Ghate et al, 2010), although mast measurements can be made in layers close to the surface (up to an altitude of a few hundred meters). The aircraft measurements are usually related to intensive field campaigns with limited spatial and temporal coverage, which restricts their usability.…”

Section: Introductionmentioning

confidence: 99%

Cloud base vertical velocity statistics: a comparison between an atmospheric mesoscale model and remote sensing observations

et al. 2011

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Abstract. The statistics of cloud base vertical velocity simulated by the non-hydrostatic mesoscale model AROME are compared with Cloudnet remote sensing observations at two locations: the ARM SGP site in central Oklahoma, and the DWD observatory at Lindenberg, Germany. The results show that AROME significantly underestimates the variability of vertical velocity at cloud base compared to observations at their nominal resolution; the standard deviation of vertical velocity in the model is typically 4-8 times smaller than observed, and even more during the winter at Lindenberg. Averaging the observations to the horizontal scale corresponding to the physical grid spacing of AROME (2.5 km) explains 70-80 % of the underestimation by the model. Further averaging of the observations in the horizontal is required to match the model values for the standard deviation in vertical velocity. This indicates an effective horizontal resolution for the AROME model of at least 10 km in the presented case. Adding a TKE-term on the resolved grid-point vertical velocity can compensate for the underestimation, but only for altitudes below approximately the boundary layer top height. The results illustrate the need for a careful consideration of the scales the model is able to accurately resolve, as well as for a special treatment of sub-grid scale variability of vertical velocities in kilometer-scale atmospheric models, if processes such as aerosol-cloud interactions are to be included in the future.

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Size Distributions and Dynamical Properties of Shallow Cumulus Clouds from Aircraft Observations and Satellite Data

Cited by 96 publications

References 38 publications

Droplet growth in warm turbulent clouds

Droplet growth in warm turbulent clouds

Entrainment and detrainment in cumulus convection: an overview

Cloud base vertical velocity statistics: a comparison between an atmospheric mesoscale model and remote sensing observations

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