Ultra-high-resolution Lidar Reveals Hidden Cloud Structures

This experimental setup at Michigan Technological University allows researchers to create and study clouds under carefully controlled conditions. Researchers from Brookhaven National Laboratory used it to demonstrate the capabilities of a new ultra-high-resolution lidar, a laser-based remote sensing instrument for studying cloud properties.
Photo Credit: Michigan Technological University

Scientists at the U.S. Department of Energy’s (DOE) Brookhaven National Laboratory and collaborators have developed a new type of lidar — a laser-based remote-sensing instrument — that can observe cloud structures at the scale of a single centimeter. The scientists used this high-resolution lidar to directly observe fine cloud structures in the uppermost portion of laboratory-generated clouds. This capability for studying cloud tops with resolution that is 100 to 1,000 times higher than traditional atmospheric science lidars enables pairing with measurements in well-controlled chamber experiments in a way that has not been possible before.

The results, published in the Proceedings of the National Academy of Sciences, provide some of the first experimental data showing of how cloud droplet properties near the tops of clouds differ from those in the cloud interior. These differences are crucial to understanding how clouds evolve, form precipitation, and affect Earth’s energy balance.

“This is the first time we’ve been able to see these cloud-top microstructures directly and non-invasively,” said Fan Yang, an atmospheric scientist at Brookhaven Lab and the lead author of the study. “These structures occur on scales smaller than those used in most atmospheric models, yet they can strongly affect cloud brightness and how likely clouds are to produce rain.”

Schematic of the cloud chamber. The Michigan Technological University Pi Cloud Chamber has a warm and humid bottom surface and a cold and humid top surface. A steady-state cloud is formed and maintained by injecting aerosol particles continuously from the side. The lidar is placed on top of the chamber and looks downward. Cloud droplet size distributions are measured by a WELAS optical particle counter.
Image Credit: Michigan Technological University

Custom-built lidar

The high-resolution lidar was conceived, designed, and constructed by Yong Meng Sua of the Stevens Institute of Technology, working closely with the Brookhaven team. It uses time-correlated single-photon counting — a technique capable of detecting individual photons backscattered from clouds by ultrafast laser pulses. Data-sampling algorithms use the photon signals to reconstruct detailed profiles of cloud structure with centimeter precision.

At the heart of the system is a custom-built laser and a highly sensitive photon-counting detector. The laser sends out ultrashort pulses of light at high repetition rates, and the detector records the arrival time of the very first photon scattered back from cloud droplets. Measuring millions of these return photons per second produces a finely resolved picture of cloud droplet distribution along the laser beam.

“This lidar is essentially a microscope for clouds,” Yang said. “Because we designed the lidar ourselves, we were able to optimize everything — from the laser system to the timing electronics — to achieve the centimeter-scale resolution needed to study cloud physics in a totally new way.”

This movie was recorded by a camera mounted above the cloud chamber, looking downward onto the cloud illuminated by a laser sheet. It clearly shows the air-cloud interface in the upper portion of the frame, where turbulent motions and downward intrusions of entrained air significantly alter the upper cloud structure relative to the bulk.
Video Credit: Michigan Technological University

Cloud chamber experiments

The team tested their new tool on well-characterized clouds generated under controlled temperature and humidity conditions in a cloud chamber at Michigan Technological University. The high-resolution lidar measurements revealed that the distribution of cloud droplets at the top of the cloud varied significantly from the more uniform structure making up the bulk of the cloud. Specifically, there were fewer cloud droplets near the top of the laboratory-generated clouds than in the bulk region.

According to the scientists, this reduction of cloud droplets near the cloud top is due to two processes: entrainment, where clear dry air above is drawn downward into the cloud, diluting the cloud and causing some droplets to evaporate; and “size sorting” due to sedimentation, where heavier droplets fall faster than lighter ones.

“In the bulk region of a cloud, turbulence is typically strong,” Yang said. “This strong turbulence allows cloud droplets of different sizes to mix efficiently and remain relatively uniformly distributed, or homogenous — similar to how stirring milk into a cup of coffee quickly mixes and homogenizes the fluid.”

Near the top of the cloud, however, turbulence is weaker, so only the smaller droplets stay suspended in the airflow while heavier ones settle out. This size sorting effect results in fewer drops and a more layered structure with local variations.

“Many atmospheric models either neglect droplet sedimentation altogether or represent droplets of different sizes with a single fall speed,” Yang said. “This simplification is reasonable in the bulk region of the cloud, where turbulence is strong, but it breaks down near the cloud top, where turbulence is weaker.”

“An inaccurate representation of cloud-top physics can introduce substantial uncertainty into model predictions of how clouds reflect sunlight and trigger rainfall,” he noted, adding that further studies will explore these potential impacts.

The Brookhaven scientists plan to expand these studies in a new cloud chamber just constructed at the Lab. “Having a cloud chamber at Brookhaven dramatically expands what we can do,” Yang said. “It allows us to iterate more quickly, validate new sensors as we build them, and deepen our understanding of cloud processes that are nearly impossible to isolate in nature.”

Key differences between observations and simulations. Data points on this graph represent corrected lidar signals at 1.2-centimeter resolution for different aerosol injection rates into the cloud chamber from low (blue) to high (red). For each injection rate, these measured signals vary significantly from the solid lines, which represent simulated lidar signals calculated under the assumption that the cloud is perfectly homogeneous in the chamber. The differences are most apparent in the uppermost region of the cloud. These fine-resolution measurements will improve understanding of cloud microphysical processes, particularly at the tops of clouds.
Image Credit: Brookhaven National Laboratory

Connecting to atmospheric measurements

Beyond providing finer scale information for improving atmospheric models, these findings will also help improve measurements in the actual atmosphere.

For example, cloud chamber measurements with the new high-resolution lidar can be used to ensure that atmospheric-sampling lidars using the same technique, including a T2 lidar built by the Brookhaven team to study cloud characteristics near the cloud base, are accurately calibrated.

“Cloud chamber experiments give us an opportunity to fully characterize clouds under well-controlled conditions and determine exactly how lidar-measured signals match up with microphysical properties such as cloud droplet number, concentration, and distribution,” Yang said. “This will help us refine the computational algorithms that relate the measurements to those properties and will improve our confidence in the atmospheric measurements.”

Funding: This work was supported by the DOE Office of Science Biological and Environmental Research program as part of the Atmospheric Systems Research initiative, along with support from the National Science Foundation and the Simons Foundation.

Published in journal: Proceedings of the National Academy of Sciences

Title: High-resolution lidar observations of sedimentation-induced size sorting of droplets near a laboratory cloud top

Authors: Fan Yang, Yong Meng Sua, Zipei Zheng, Jesse Anderson, Hamed Fahandezh Sadi, Jae Min Yeom, Suryadev Pratap Singh, Pei Hou, Will H. Cantrell, Ernie R. Lewis, Alex B. Kostinski, and Raymond A. Shaw

Source/Credit: Brookhaven National Laboratory

Reference Number: tech122325_01

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