School of Earth and Environment

Climate and Atmospheric Science (ICAS) PhD Projects

Boundary Layer Fluid Dynamics: Large Eddy Modelling of Entrainment Mixing

Supervisors: Dr Ian Brooks

Entrainment at the top of the atmospheric boundary layer (BL) is a controlling process for BL development. It is the primary mechanism by which the BL deepens and a dominating factor in the development, distribution, and dissipation of climatically important stratocumulus clouds, particularly over the oceans where they play an important role in governing the surface energy balance. Accurate representation of entrainment in models is thus essential to correct representation of cloud distributions and hence the global radiative energy budet. Although important, entrainment is not well understood and is poorly represented in both climate and numerical weather prediction models; there remain fundamental questions regarding the controlling processes (Angevine 2007). Entrainment proceeds via turbulent mixing across the stably stratified temperature inversion that caps the boundary layer. It is inherently sporadic in nature, occurring through discrete mixing events, and is thus difficult to sample effectively.

Direct, in situ measurement of the entrainment rate is almost impossible, and it must be inferred from other measurements. A common approach has been to use remote sensing systems such as lidar or sodar to determine properties of the entrainment zone – the region of active mixing between the BL and free troposphere - such as its depth, and to relate these to the mean properties of the boundary layer. Such approaches have the advantage of being relatively straightforward, but a lack of consistency in methodology and the differing measurement types and sampling resolutions of different instrumentation systems has made it difficult to compare studies directly and to build a single coherent picture of entrainment physics. An alternative approach to direct measurement has been the use of Large Eddy Simulation (LES) models to study the entrainment process. These have the advantage of allowing control of the forcing conditions, and relatively straightforward evaluation of the entrainment rate – although high resolution is required to resolve the turbulent processes properly, particularly in cloud topped cases. Interpretation of both observational measurements and large eddy simulations and comparison of results from different studies is hampered by a lack of consistent diagnostic techniques; part of this study will focus on evaluating different methods and developing new analysis techniques.

Recent developments in signal processing techniques have allowed detailed information on the entrainment zone to be determined for the first time (Brooks 2003, Grabon et al. 2010), and the development of new measures of entrainment zone structure (Brooks and Fowler, 2007). Combined with advances in remote sensing technology, and computational power these provide the potential to gain new insights into the physics of entrainment processes.

Figure 1. (a) a cross section of lidar backscatter signal and the locations of the upper (white) and lower (black) limits of the local entrainment zone determined via the Brooks (2003) wavelet algorithm; the red dots mark the location of a common measure of boundary layer top – the location of the peak in the vertical gradient of the lidar backscatter. (b-f) individual lidar profiles at the locations marked by vertical lines on (a), with the local entrainment zone limits indicted by dashed lines, and the BL top by a circle.

This study will utilise large eddy simulations both to study the detailed nature of entrainment dynamics and to develop new diagnostic techniques applicable to lidar measurements. Lidar data from a variety of field measurement campaigns will be used to test the application of these techniques to real-world situations. Objectives are to:

  • Understand the relationships between entrainment rate and entrainment zone properties and the controlling parameters: surface buoyancy flux, wind shear, inversion strength.
  • To develop diagnostic techniques applicable to lidar measurements of the boundary layer for retrieval of entrainment zone properties and entrainment rate.
  • To develop parameterisations of entrainment for use in large scale models where turbulent processes are cannot be resolved.

Figure 2. (left) local boundary layer depth (m), and (right) local entrainment zone depth (m) from a large eddy simulation of a convective boundary layer.


References

  • Angevine, W. M. (2007), Transitional, entraining, cloudy, and coastal boundary layers, Acta Geophys., 56, 2-20, doi: 10.2478/s11600-007-0035-1.
  • Brooks, I. M., 2003: Finding Boundary Layer Top: Application of a Wavelet Covariance Transform to Lidar Backscatter Profiles. J. Atmos. Oceanic Technol., 20, 1092-1105.
  • Brooks and Fowler, 2007: A new measure of entrainment zone structure, Geophysical Research Letters, 34, L16808, doi:10.1029/2007GL030958.
  • Grabon, J. S., K. J. Davis, C. Kiemle, G. Ehret (2010), Airborne Lidar Observations of the Transition Zone Between the Convective Boundary Layer and Free Atmosphere During the International H2O Project (IHOP) in 2002. Bound.-Layer Meteorol., 134, 61-83, doi: 10.1007/s10546-009-9431-1.