Researchers used long-term ARM data to gain a new understanding of the vertical structure of turbulence in the convective boundary layer.
Vertical velocity, the speed of upward and downward air motions in the atmosphere, plays a critical role in many atmospheric processes. In the near-surface layer of the atmosphere known as the boundary layer, variations in vertical velocity are generally associated with thermals generated by surface heating, turbulence induced by wind shear, or a combination of both processes. The distribution of vertical velocity is a key factor in representations of cumulus clouds in regional and global models, but few long-term measurements of vertical velocity within the convective boundary layer are available to evaluate and improve the way vertical velocity is represented in these models. A research team led by scientists at the U.S. Department of Energy’s Pacific Northwest National Laboratory used data from a full seasonal cycle at one location to evaluate long-standing assumptions about the structure of turbulence and vertical velocity in the daytime convective boundary layer.
The data offer new insight into the vertical structure of turbulence in the convective boundary layer. Scientists studied details of the distributions of vertical velocity and found dependence on time of day and weather conditions such as wind shear at the top of the boundary layer. The results also highlight that care is needed when applying traditional scaling approaches during periods, such as morning, when the properties of the boundary layer are changing. Researchers can use the new data set to assess turbulence treatment in large-eddy simulation, regional, and global models, as well as evaluate existing theories related to boundary layer turbulence.
Over flat land such as the U.S. Great Plains, vertical velocity variations within the daytime convective boundary layer have often been connected to the intensity of the surface heating and/or wind shear (variation in wind speed or direction with height). To evaluate these assumptions, researchers analyzed a year’s worth of data from the DOE Atmospheric Radiation Measurement (ARM) Facility’s Doppler lidar at the ARM Southern Great Plains atmospheric observatory in Oklahoma. Scientists examined details of the distributions of vertical velocity, including the mean, standard deviation, skewness, and kurtosis (how the data compare with a normal distribution), as a function of different variables. Scientists found that mean, skewness, and kurtosis were dependent on time of day, season, shear stress, stability, and shear at the boundary layer top. Such detailed analyses require a long data record, which was not attainable with previous lidar deployments or research aircraft campaigns. Researchers can use this new data set to better understand the nature of the turbulence and evaluate models with grid spacings from tens of meters to tens of kilometers.
Contacts (BER PM)
Atmospheric System Research
Atmospheric System Research
Atmospheric Radiation Measurement (ARM) Facility
Pacific Northwest National Laboratory
The U.S. Department of Energy Office of Science, Biological and Environmental Research supported this research as part of the Atmospheric System Research (ASR) program. Data were obtained from the Atmospheric Radiation Measurement (ARM) Facility, a DOE Office of Science user facility sponsored by the Office of Biological and Environmental Research.
L.K. Berg, R.K. Newsom, D.D. Turner, “Year-Long Vertical Velocity Statistics Derived from Doppler Lidar Data for the Continental Convective Boundary Layer.” Journal of Applied Meteorology and Climatology, in press (2017). [DOI: 10.1175/JAMC-D-16-0359.1] (Reference link)
SC-23.1 Climate and Environmental Sciences Division, BER
BER supports basic research and scientific user facilities to advance DOE missions in energy and environment. More about BER
Aug 24, 2019
New Approach for Studying How Microbes Influence Their Environment
A diverse group of scientists suggests a common framework and targeting of known microbial processes [more...]
Aug 08, 2019
Nutrient-Hungry Peatland Microbes Reduce Carbon Loss Under Warmer Conditions
Enzyme production in peatlands reduces carbon lost to respiration under future high temperatures. [more...]
Aug 05, 2019
Amazon Forest Response to CO2 Fertilization Dependent on Plant Phosphorus Acquisition
AmazonFACE Model Intercomparison. The Science Plant growth is dependent on the availabi [more...]
Jul 29, 2019
A Slippery Slope: Soil Carbon Destabilization
Carbon gain or loss depends on the balance between competing biological, chemical, and physical reac [more...]
Jul 15, 2019
Field Evaluation of Gas Analyzers for Measuring Ecosystem Fluxes
How gas analyzer type and correction method impact measured fluxes. The Science A side- [more...]
List all highlights (possible long download time)