# Planetary Boundary Layer

## Radar observations of turbulence in the cloud-capped PBL

 Click image for a larger version. Figure 50. Profile of turbulence dissipation rate measured by the WCR (solid line) and in situ measurements (triangles) during Flight 7 of DYCOMS-2. The predominant TKE production terms are also displayed: buoyancy (circles; the thin dashed line is a least squares 3rd-order polynomial fit) and shear (thick dashed line). Cloud is indicated by the shaded area. The agreement with in situ measurements is excellent throughout the lower 2/3 of the STBL. The vertically integrated dissipation agrees well with the sum of the vertically integrated buoyancy and shear production terms.

The stratocumulus-topped boundary layer (STBL), which prevails in the subtropics in regions where the underlying ocean is much colder than the overlying atmosphere, is an important component of the global climate system. However, attempts to quantify and model the processes that control its evolution have fallen short of what is needed for accurate climate prediction. One important issue is the role that turbulence plays in entrainment of warm dry air from the overlying free troposphere. A key to understanding this is to quantify the turbulence kinetic energy (TKE) budget in the STBL. In the Dynamics and Chemistry of the Marine Stratocumulus (DYCOMS-2) Experiment, conducted off the California coast in July 2001, the Wyoming Cloud Radar (WCR) was mounted on the NCAR C-130 aircraft and used to probe the turbulence structure of the STBL. The downward-looking beams were used to resolve droplet velocities throughout regions of the STBL containing droplets. These measurements contain velocity fluctuations due to both real air velocity fluctuations as well as a contribution due to variations in droplet fall velocity. Donald Lenschow and Marie Lothon (visitor from France), along with Gabor Vali and David Leon (both of University of Wyoming) have developed techniques to estimate the fall velocity contribution, and to correct the radar velocity measurements for volume averaging and noise. As a result, they have been able to estimate TKE dissipation throughout the STBL on a day with relatively uniform drizzle distribution, as shown in Figure 50. This is an essential step in resolving the TKE budget.

## The interfacial structure of the cloud-capped PBL

A commonly-adopted idealization for modeling the stratocumulus-topped PBL (STBL) is that its upper interface is distinguished by all of the following conditions: (1) it separates cloudy and clear air, (2) occurrence of the sharpest jump (maximum-gradient) in local soundings, (3) it separates turbulent motions from the free-atmospheric non-turbulent flow, and (4) it delineates the entrainment zone. Existing theories of cloud-top entrainment instability (CTEI) rely heavily on the assumption that a local sharp-edged interface separates two distinct air masses: one turbulent and completely saturated, and the other non-turbulent and completely unsaturated. How valid is this idealization? Are the cloud-top interface, maximum-gradient interface and turbulence-laminar interface the same? Using large-eddy simulation (LES), Chin-Hoh Moeng, Bjorn Stevens (University of California, Los Angeles) and Peter Sullivan investigated this issue. They found that the cloud-top interface is always below the maximum-gradient interface, and the maximum-gradient interface below the turbulent-mixing interface (Figures 51and 52). The differences between these interfaces are typically larger than 20 meters. This interfacial property could be significant in modeling the entrainment rate and cloud-top entrainment instability of the STBL.

 Click image for larger version. Figure 51. Contours of (top panels) cloud-top interface $z_{\rm lwc}$ and maximum-gradient interface $z_{\rm mgd}$, and (bottom panels) twoturbulent-mixing interfaces $z_{\rm mix}$ diagnosed from Scalars A and B. The white area in the $z_{\rm lwc}$ contours represent cloud-free columns. Click image for larger version. Figure 52. Various interfacial heights along four separate horizontal segments linked together from the case shown in Fig. 1: Dark-solid curve is the cloud-top interface, dark-dotted curve is the maximum-gradient interface, and the two light-color curves mark the turbulent-mixing interface diagnosed from two passive scalars.

## Evaluation of large-eddy simulation via observations of cloud-capped PBL

C.-H. Moeng participated in the FY04 intercomparison of LES solutions of marine stratocumulus organized by the GCSS Boundary-Layer Cloud Working Group (see http://www.atmos.washington.edu/%7ebreth/GCSS/GCSS.html). This intercomparison
study, led by Bjorn Stevens (UCLA), focused on evaluation of large-eddy simulations using observations of nocturnal marine stratocumulus from DYCOMS-II. The cloud case studied here is particularly challenging for LES because the cloud-top jump condition lies within the controversial range between solid and broken cloud regimes. Many LESs failed to produce the observed solid cloud layer, which led to an important conclusion that most LESs over-estimate mixing at the cloud top due to either numerical diffusion, or subgrid-scale mixing (or both). Too much mixing across the cloud top produced a drier PBL and hence a broken cloud layer.

## Increasing the albedo and longevity of low-level maritime clouds

John Latham has further extended his research into a novel idea for the amelioration of global warming by the advertent and controlled enhancement of the albedo A and longevity L of low-level maritime clouds. The consensus view of the scientists participating in the International Symposium on Global Warming Mitigation, held in Cambridge, England, in January 2004--at which Latham presented a paper on this work--was that this approach held promise and should be funded for field tests. More detailed calculations coupled with computer modeling with the UK Meteorological Office GCM, support the quantitative validity of the proposed technique, which involves increasing the droplet concentration in such clouds, with a corresponding increase in both A and L: and thus cooling. The idea involves the dissemination at the ocean surface of small seawater droplets in sufficient quantities to act as the dominant CCN on which cloud droplets form. Satellite control of the overall dissemination rate is envisaged. Collaborators include Dr. Keith Bower & Prof. Tom Choularton (both UMIST, Manchester, UK), Dr. Alan Blyth, Dr. Alan Gadian & Prof. Mike Smith (all University of Leeds, UK), Prof. Stephen Salter, (University of Edinburgh, UK) and Dr. Andy Jones (Hadley Climate Centre, Meteorological Office, UK). If this technique were to prove workable on the scales required, it could be of great societal importance.

## Dynamical behavior of the marine stratocumulus regime

A key dynamical variable that regulates marine stratiform cloud is the large-scale divergence in the boundary layer. In DYCOMS-II, two independent techniques are being used to estimate divergence: First, the divergence was obtained for all the flights with a standardized flight pattern in an effort spearheaded by Ian Faloona (University of California, Davis) from the difference between the entrainment velocity and the time rate of change of cloud-top height. The entrainment velocity was obtained from measurements of scalar fluxes extrapolated to cloud-top and the jump in scalar concentration across cloud top. Second, measurements of spatial variations in the mean wind field obtained from circular flight paths at several levels within the boundary layer are being used by D. Lenschow, Bjorn Stevens and Verica Savic-Jovcic (both of the University of California, Los Angeles) to directly measure the divergence. They have found that this measurement is on the edge of what is currently technically feasible with the NCAR C-130 aircraft measuring system, but by recalibrating the standard wind measurements they obtain a consistent pattern of divergence through the set of DYCOMS-II flights.

## LES of Marine Boundary Layers with Swell

 Click image for a larger version. Figure 53. Vertical profiles of the mean wind components in the atmospheric boundary layer for flow over waves from LES with a constant geostrophic wind of 5 m/s. The surface conditions are: a) a flat surface; b) a stationary wave; c) swell moving along the U direction at 12.5 m/s; and d) flow over swell with slight convection. [right panel] Total (resolved plus SGS) vertical momentum flux profiles from LES.

Peter Sullivan, James Edson (Woods Hole Oceanographic Institute), James McWilliams (University of California, Los Angeles), and Chin-Hoh Moeng continued the analysis of their LES solutions for atmospheric flow over surface waves. The emphasis is on light-wind conditions with fast moving swell as observed during the low-wind Coupled Boundary Layers Air-Sea Transfer (CBLAST) field campaign. The simulations span a range of surface conditions and atmospheric stratifications. They have also initiated a comparison with the surface layer data gathered from the Air-Sea Interaction Tower used during CBLAST. LES results dramatically demonstrate (Figure 53) that sea state modulates the magnitude and orientation of the mean wind and momentum flux in light winds. For example, at 10 m height, the surface wind, U, is to the left of the geostrophic wind (that is, the normal component V is positive, where the U direction is along the geostrophic wind) as expected for flow over rough surfaces and stationary waves while the opposite is observed in the presence of swell, where the swell here is moving along the geostrophic wind direction at 12.5 m/s. In this case, the surface-layer wind is slightly to the right of the geostrophic wind. The vertical profiles also show that the impact of swell is not confined to the surface layer but can extend to considerable heights above the surface. With swell, the wind component along the geostrophic profile exhibits a low-level jet around 20 m height, which disappears with slight convection. The weak mean shear in the swell-driven (neutrally stratified) PBL generates little turbulent kinetic energy (TKE) in the region above the jet, an important result of the swell-induced changes in the marine surface layer. Profiles of the total vertical momentum flux further illustrate the important consequences swell has for the momentum balance in the atmospheric PBL. The variation and signs of both components of the momentum flux are consistent with the formation of a low-level jet and in fact are mandatory in order to achieve a steady balance between the pressure gradient forcing and stress divergence. These results demonstrate that wave state needs to be taken into account when parameterizing PBL processes in mesoscale and global scale atmospheric models

## Sound propagation in a turbulent atmosphere

Edward Patton and P. Sullivan (in collaboration with Army Research Laboratory, Army Corps of Engineers, Sandia National Laboratory and NOAA/ETL) are using high-resolution large-eddy simulation to investigate the influence of turbulence on atmospheric sound propagation. Simulations employ more than 120 million gridpoints. Sound is propagated through the LES-derived atmosphere using a newly developed finite difference algorithm appropriate for modeling acoustic waves in moving, inhomogeneous 3d media. Although the effects are subtle, atmospheric heterogeneity in sound speed, density, and velocity cause low-amplitude pressure events to trail the main diverging wavefronts (Figure 54 animation). We are actively investigating the influence of atmospheric stability on sound propagation and future research will examine the impact of vegetation.

 Click image for larger animation. Figure 54. Time evolution of acoustic pressure field for a 20-Hz dominant zero-phase wavelet source propagating through an unstable atmosphere ($z_i/L$ = -6) generated by large-eddy simulation. The ground surface is assumed to be perfectly reflecting. Resulting from atmospheric heterogeneities, for times greater than 0.4 seconds, low-amplitude pressure events trail the main diverging wavefronts.

## Observations of two-point turbulence statistics in the clear-air PBL

 Click image for a larger version. Figure 55. Vertical versus horizontal integral length scales of the vertical air velocity normalized by the PBL depth observed with a ground-based Doppler lidar (HRDL) within the mid-day CBL during 11 days in LIFT. A total of nine levels within a 250 m layer are used for this analysis. The solid line is the theoretical ratio for isotropic turbulence; the dashed line is the least squares fit to the observations constrained to pass through the origin.

The turbulent eddies that transport heat, momentum and trace constituents through the convective boundary layer (CBL) are anisotropic. One way to quantify this anisotropy is to calculate two-point turbulence statistics such as the spatial coherence of the air velocity components. Measurements of these statistics, however, are difficult to obtain with traditional in situ measurements techniques. Doppler radars and lidars, however, can measure the radial component of air velocity as a function of distance from the sensor. Marie Lothon (MMM visitor), D. Lenschow, and Shane Mayor (ATD) have used measurements of the vertical air velocity from a ground-based zenith-pointing High Resolution Doppler Lidar (HRDL) deployed during the Lidar In Flat Terrain (LIFT) experiment in central Illinois in the summer of 1996 to measure the coherence of the vertical velocity in the vertical, as well as its integral scales in both the horizontal and vertical directions for twelve days during LIFT. They observed that the measured vertical coherence tends to be larger than predicted by isotropic models except at very small scales. They also found that the ratio of the integral scale of vertical velocity along the vertical direction to that in the along-wind direction is more than twice as large as would be the case for isotropic turbulence (Figure 55); that is; the eddies are stretched in the vertical relative to the horizontal. The high correlation of this relationship means that the vertical integral scale can be estimated from the more-easily-measured horizontal integral scale.