Published in Geophysical Research Letters, “Estimation of cloud fraction profile in shallow convection using a scanning cloud radar” details some of the problems inherent in measuring shallow convective clouds with radars and proposes a methodology to address the issues. The paper uses data from the Southern Great Plains atmospheric observatory and is also the first publication to use data from LASSO, which released a set of initial results in July.
Bouncing Radar Waves on Water Droplets
Being able to accurately estimate and represent shallow convection is important, as it plays a key role between the boundary layer and free atmosphere, and also affects incoming shortwave radiation. Most meteorological models don’t “zoom in” enough to catch all the detail, but pairing LES with accompanying measurements—like LASSO—can provide the necessary information.
Getting those measurements can be difficult, though. “In a sense, LASSO wants information about the clouds that is not derived by single point (profiling) measurements, but rather derived from a large volume of data,” co-author Pavlos Kollias, Stony Brook University and leader of the ARM radar science group, said. “This suggests the use of scanning sensors like radars and lidars and led to our recent paper.”
Using scanning radars doesn’t come without its own challenges. The ability of the radar to detect clouds weakens with range causing the radar to underestimate the cloud cover farther away from its position.
“The radar sends out radio waves, and those have to bounce off of water particles in the air to generate a return,” co-author and LASSO principal investigator Bill Gustafson, Pacific Northwest National Laboratory, explained. “For these small clouds, sometimes there just isn’t enough moisture to get an accurate measurement.”
The paper outlines the problem of weakening radar signal and then proposes an optimal method for scanning to compensate for it. “It’s really making the most of these instruments and accounting for clouds that they can barely see,” Gustafson said.
The technique is a general one, so while it was evaluated at SGP, it could benefit scanning radars anywhere.
Models Improving Measurements, Measurements Improving Models
“I think this is the first of many studies that will challenge the representativeness of profiling observations for studying broken cumulus clouds. ARM already had the foresight to develop a megasite at the SGP to address these cloud sampling issues,” Kollias said, but he didn’t want to lose sight of the big picture.
“In a broader sense, the LASSO project literally acts as a lasso (restrainer). The LASSO project provided a detailed list of measurements required to accomplish the modeling objectives, which subsequently brought discipline to the ARM observationalists and forced us to think in a creative way how to best address and satisfy the modeling needs in terms of measurements.”
LASSO provides the data needed to compare models to measurements, making it easier to work between the two areas. “It’s helpful for radar scientists to be able to just ask for a simulation over a certain time period,” Gustafson said, and similarly modelers can access quality measurements.
“This is the first time that a large observational program, like ARM, supports its own large, systematic modeling activity,” Kollias added. “This automatically generates a closed loop between modeling, theory and observations, accelerating the dialogue between modeling needs and observational capabilities and limitations.”
Even though LASSO’s first release was only a few months ago, work is already being done that shows its value. This first paper will be one of many research projects to come out of and benefit from ARM’s innovative pairing of modeling and measurements.
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The ARM Climate Research Facility is a national scientific user facility funded through the U.S. Department of Energy's Office of Science. The ARM Facility is operated by nine Department of Energy national laboratories, including the Pacific Northwest National Laboratory, which manages ARM's radar facilities.
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