A Deeper Look Into Shallow Boundary Layer Clouds
Bretherton, C. S., University of Washington
Cloud Distributions/Characterizations
Cloud Modeling
Bretherton, C. S., J. R. McCaa, and H. Grenier. A New Parameterization for Shallow Cumulus Convection and Its Application to Marine Subtropical Cloud-Topped Boundary Layers. Part I: Description and 1D Results, Monthly Weather Review, 132(1), 864-882, 2004, doi: 10.1175/1520-0493(2004)132<0864:ANPFSC>2.0.CO;2.
McCaa, J. R., and C. S. Bretherton. A New Parameterization for Shallow Cumulus Convection and Its Application to Marine Subtropical Cloud-Topped Boundary Layers. Part II: Regional Simulations of Marine Boundary Layer Clouds, Monthly Weather Review, 132(1), 883-896, 2004, doi: 10.1175/1520-0493(2004) 132<0883:ANPFSC>2.0.CO;2.
Figure 1
Shallow cumulus clouds are the most abundant of all tropical clouds. Though not deep enough to develop significant precipitation, they play a major role in temperature, humidity, cloud cover and winds, and therefore, present a significant influence on the Earth's radiation budget. They are also among the most difficult clouds to simulate well in large-scale climate models, representing an important component of model uncertainty in simulations of future climate change. Scientists funded jointly by DOE's Atmospheric Radiation Measurement Program and the National Aeronautics and Space Administration developed a new parameterization of convection within shallow cumulus clouds that demonstrates improvement in the simulation of these clouds.
The new scheme is based on the fundamental physics of boundary layer cloud formation—it statistically parameterizes the rise of buoyant air parcels or plumes from the ocean surface. The researchers coupled this parameterization to an existing model describing turbulence and entrainment by a convective plume as it rises through the boundary layer. Model results were validated by comparing them to existing large-eddy simulations (which are highly detailed simulations of plume behavior), demonstrating that variations in lateral mixing at different heights can be captured by implementing a buoyancy-sorting mechanism in the updraft cloud model. When subsequently implemented in a mesoscale model, the new scheme provided results closer to observed conditions than previous schemes.
Previous models of shallow cumulus convection used an eddy diffusivity formulation or a moist adjustment scheme to predict cloud occurrence. The new model uses a simple cloud model coupled to an algorithm that specifies mass flux through the cloud. As a buoyant plume rises, turbulence at the plume boundary causes mixing with the surrounding environment. Environmental components that have positive buoyancy remain entrained in the rising plume. Components with negative buoyancy are detrained or rejected from the plume and tend to sink to an altitude of neutral buoyancy. The shallow cumulus parameterization contains three novel features: (1) the cloud-base mass flux is determined based on surface layer turbulent kinetic energy and convective inhibition near the cloud base, (2) lateral mixing is calculated with a new buoyancy sorting scheme, and (3) modeling the mixing of updrafts above the level of neutral buoyancy is enhanced.
The new parameterizations were incorporated into the fifth-generation Pennsylvania State University-NCAR Mesoscale Model (MM5). In a 3-month simulation of the northeast and southeast Pacific Ocean, the model was applied using several existing schemes and the new scheme with two different sets of model parameters. The previous schemes led to overly thick, bright stratocumulus clouds and too low a trade inversion. While the new model thinned the stratocumulus clouds to observed albedos, it still overestimated low-cloud amounts in the trade-cumulus region.
In figure 1, estimates of short wave cloud radiative forcing (SWCF) over the Pacific are indicated by shaded areas; the dotted lines indicate the error from observed conditions. Compared to observations, schemes (a)-(d) using parameters from the original MM5 overestimate SWCF, as shown by the bright clouds. The new mass flux model (e) comes closer to observations, producing fewer bright areas. Adding the new shallow cumulus parameters (f) further decreases the albedo and shows the least deviation from observations. This test confirms the importance of shallow cumulus turbulence and mixing parameters in accurately modeling weather. Future research using millimeter-wavelength Doppler radar observations is expected to fine tune the parameterization and increase the accuracy of the results.
