Research Interests:

  • Boundary layer convection and clouds
  • Parameterization of convection
  • Stochastic parameterization
  • Statistical ensembles
  • Convective flows in the gray zone

 

Controls on the distribution of shallow cumulus clouds by a moist convective heat cycle

The probability distribution of the cloud base mass flux p(m) in shallow cumulus cloud ensembles differs in the conditions over the tropical ocean and over mid-latitude continental regions. Based on the findings from large eddy simulations (LES), the distribution over the ocean has a concave shape while the distribution over land has a straight line shape on a log-log plot (Fig. 1). These differences can be explained using the formalism of a moist convective heat cycle.

The main parameter that sets the shape of p(m) is the surface Bowen ratio B, the ratio between the sensible and the latent turbulent heat fluxes. The Bowen ratio controlls the efficiency of the moist convecive heat cycle η and thereby sets the average mass flux per cloud <m>:

<m> ~ C η Fsfc / Δh

C - constant of proportionality

Fsfc - surface turbulent heat flux

Δh - excess of the moist static energy within convective updrafts

Finaly, the overal shape of the distribution is set by the value of <m>. For more details see [1].

 

Stochastic parameterization of shallow convection

Horizontal grid spacing of numerical atmospheric models is not fine enough to resolve atmospheric convection and clouds, which therefore need to be parameterized. By means of a deterministic convection parameterization, the effects of the unresolved scales are usually represented as a bulk quantity or as an ensemble average. How well a bulk formulation will describe the sub-grid state depends mostly on the grid resolution of the model and the large scale atmospheric situation. In most cases, the ensemble average is not the most probable outcome of the subgrid processes, and as the model resolution increases, the spread around the average becomes larger. To represent this spread around the average outcome, a stochastic approach based on the concepts from statistical mechanics is used [2]. This approach is developed by combining the theory of the statistical ensembles with findings from the Large Eddy Simulations (LES). Cumulus clouds are subsampled from the cloud population distribution, so that depending on the grid resolution, the resulting distribution of the subgrid convective states takes various shapes (Fig. 2). 

References

[1] Sakradzija, M., and C. Hohenegger, What determines the distribution of shallow convective mass flux through cloud base?, J. Atmos. Sci., https://doi.org/10.1175/JAS-D-16-0326.1, 2017.

[2] Sakradzija, M., Seifert A. and Heus T.: Fluctuations in a quasi-stationary shallow cumulus cloud ensemble, Nonlin. Processes Geophys., 22, 65-85, 2015, doi:10.5194/npg-22-65-2015