The science behind snowflakes
In a study that could enhance weather forecasting, Utah researchers discover that how snowflakes move is astonishingly predictable.
IMAGE:
GRADUATE STUDENT RYAN SZCZERBINSKI EXAMINES INSTRUMENTATION CALLED A DIFFERENTIAL EMISSIVITY IMAGING DISDROMETER, OR DEID, DEVELOPED BY UNIVERSITY OF UTAH RESEARCHERS AND INSTALLED AT ALTA NEAR THE TOP OF LITTLE COTTONWOOD CANYON. THE EQUIPMENT MEASURES THE HYDROMETEOR MASS, SIZE AND DENSITY OF SNOWFLAKES.
view moreCREDIT: TIM GARRETT, UNIVERSITY OF UTAH
Tim Garrett has devoted his scientific career to characterizing snowflakes, the protean particles of ice that form in clouds and dramatically change as they fall to Earth.
Now the University of Utah atmospheric scientist is unlocking the mystery of how snowflakes move in response to air turbulence that accompanies snowfall using novel instrumentation developed on campus. And after analyzing more than half a million snowflakes, what his team has discovered has left him astonished.
Rather than something incomprehensibly complicated, predicting how snowflakes move proved to be surprisingly simple, they found.
“How snowflakes fall has attracted a lot of interest for many decades because it is a critical parameter for predicting weather and climate change,” Garrett said. “This is related to the speed of the water cycle. How fast moisture falls out of the sky determines the lifetime of storms.”
'Letters sent from Heaven'
The famed Japanese physicist Ukichiro Nakaya termed snow crystals “letters sent from heaven” because their delicate structures carry information about temperature and humidity fluctuations in the clouds where crystal basal and prism facets competed for water vapor deposition.
While every snowflake is believed to be completely unique, how these frosty particles fall through the air—as the accelerate, drift and swirl—follows patterns, according to new research by Garrett and colleagues in the College of Engineering. Snowflake movement has important implications for weather forecasting and climate change, even in the tropics.
“Most precipitation starts as snow. How question of how fast it falls affects predictions of where on the ground precipitation lands, and how long clouds last to reflect radiation to outer space,” Garrett said. “It can even affect forecasts of a hurricane trajectory.”
Also involved with the research are Dhiraj Singh and Eric Pardyjak of the U’s Department of Mechanical Engineering
To study snowflake movement, the team needed a way to measure individual snowflakes, which has been a challenging puzzle for years.
“They have very low masses. They may only weigh 10 micrograms, a hundredth of a milligram, so they cannot be weighed with very high precision,” Garrett said.
Working with engineering faculty, Garrett developed instrumentation called the Differential Emissivity Imaging Disdrometer, or DEID, which measures snowflakes’ hydrometeor mass, size and density. This device has since been commercialized by a company Garrett co-founded called Particle Flux Analytics. The Utah Department of Transportation has deployed the equipment in Little Cottonwood Canyon to help with avalanche forecasting, he said.
For Garrett’s field experiments, his team set it up at Alta, the famed ski destination and Utah's snowiest place for the winter of 2020-21. The instrumentation was deployed alongside measurements of air temperature, relative humidity and turbulence, and placed directly beneath a particle tracking system consisting of a laser light sheet and a single-lens reflex camera.
“By measuring the turbulence, the mass, density and size of the snowflakes and watching how they meander in the turbulence,” Garrett said, “we are able to create a comprehensive picture that hadn't been able to be obtained before in a natural environment before.”
The findings were not what the team expected.
Despite the intricate shapes of snowflakes and the uneven movement of the air they encounter, the researchers found they could predict how snowflakes would accelerate based on a parameter known as the Stokes number (St), which reflects how quickly the particles respond to changes in the surrounding air movements.
When the team analyzed the acceleration of individual snowflakes, the average increased in a nearly linear fashion with the Stokes number. Moreover, the distribution of these accelerations could be described by a single exponential curve independent of Stokes number.
The researchers found that the same mathematical pattern could be connected to how changing snowflake shapes and sizes affect how fast they fall, suggesting a fundamental connection between the way the air moves and how snowflakes change as they fall from the clouds to the ground.
“That, to me, almost seems mystical,” Garrett said. “There is something deeper going on in the atmosphere that leads to mathematical simplicity rather than the extraordinary complexity we would expect from looking at complicated snowflake structures swirling chaotically in turbulent air. We just have to look at it the right way and our new instruments enable us to see that.”
Garrett’s study, titled “A universal scaling law for Lagrangian snowflake accelerations in atmospheric turbulence,” is to be published in the journal Physics of Fluids, published by the American Institute of Physics. Funding came from the National Science Foundation.
JOURNAL
Physics of Fluids
METHOD OF RESEARCH
Observational study
SUBJECT OF RESEARCH
Not applicable
ARTICLE TITLE
universal scaling law for Lagrangian snowflake accelerations in atmospheric turbulence
ARTICLE PUBLICATION DATE
19-Dec-2023
COI STATEMENT
The DEID technology is protected through patent US20210172855A1 co-authored with D.K.S., E.R.P., and T.J.G. and is commercially available through Particle Flux Analytics, Inc. T.J.G. is a co-owner of Particle Flux Analytics, Inc. which has a license from the University of Utah to commercialize the DEID.
Snowflakes swirling in turbulent air as they fall through a laser light sheet. Credit: Singh et al.
Snowflake accelerations mysteriously follow a predictable pattern.
Peer-Reviewed PublicationVIDEO:
SNOWFLAKES SWIRLING IN TURBULENT AIR AS THEY FALL THROUGH A LASER LIGHT SHEET.
view moreCREDIT: SINGH ET AL.
WASHINGTON, Dec. 19, 2023 – A winter wonderland calls to mind piles of fluffy, glistening snow. But to reach the ground, snowflakes are swept into the turbulent atmosphere, swirling through the air instead of plummeting directly to the ground.
The path of precipitation is complex but important to more than just skiers assessing the potential powder on their alpine vacation or school children hoping for a snow day. Determining snowflake fall speed is crucial for predicting weather patterns and measuring climate change.
In Physics of Fluids, from AIP Publishing, researchers from the University of Utah report snowflake accelerations in atmospheric turbulence. They found that regardless of turbulence or snowflake type, acceleration follows a universal statistical pattern that can be described as an exponential distribution.
“Even in the tropics, precipitation often starts its lifetime as snow,” said author Timothy Garrett. “How fast precipitation falls greatly affects storm lifetimes and trajectories and the extent of cloud cover that may amplify or diminish climate change. Just small tweaks in model representations of snowflake fall speed can have important impacts on both storm forecasting and how fast climate can be expected to warm for a given level of elevated greenhouse gas concentrations.”
Set up in a ski area near Salt Lake City, the team battled an unprecedented 900 inches of snow. They simultaneously filmed snowfall and measured atmospheric turbulence. Using a device they invented that employs a laser light sheet, they gathered information about snowflake mass, size, and density.
“Generally, as expected, we find that low-density ‘fluffy’ snowflakes are most responsive to surrounding turbulent eddies,” said Garrett.
Despite the system’s complexity, the team found that snowflake accelerations follow an exponential frequency distribution with an exponent of three halves. In analyzing their data, they also discovered that fluctuations in the terminal velocity frequency distribution followed the same pattern.
“Snowflakes are complicated, and turbulence is irregular. The simplicity of the problem is actually quite mysterious, particularly given there is this correspondence between the variability of terminal velocities – something ostensibly independent of turbulence – and accelerations of the snowflakes as they are locally buffeted by turbulence,” said Garrett.
Because size determines terminal velocity, a possible explanation is that the turbulence in clouds that influences snowflake size is related to the turbulence measured at the ground. Yet the factor of three halves remains a mystery.
The researchers will revisit their experiment this winter, using a mist of oil droplets to obtain a closer look at turbulence and its impact on snowflakes.
Field site near Salt Lake City where researchers battled 900 inches of snow to collect their data.
CREDIT
Singh et al.
The article “A universal scaling law for Lagrangian snowflake accelerations in atmospheric turbulence” is authored by Dhiraj Kumar Singh, Eric R. Pardyjak, and Timothy Garrett. It will appear in Physics of Fluids on Dec. 19, 2023 (DOI: 10.1063/5.0173359). After that date, it can be accessed at https://doi.org/10.1063/5.0173359.
ABOUT THE JOURNAL
Physics of Fluids is devoted to the publication of original theoretical, computational, and experimental contributions to the dynamics of gases, liquids, and complex fluids. See https://pubs.aip.org/aip/pof.
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JOURNAL
Physics of Fluids
ARTICLE TITLE
A universal scaling law for Lagrangian snowflake accelerations in atmospheric turbulence
ARTICLE PUBLICATION DATE
19-Dec-2023
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