The science of snowflakes and their astonishingly predictable movement

Snowflakes and the science behind their formation have long captivated us, with their intricate structures and graceful descent from the clouds to the Earth’s surface. Tim Garrett, an atmospheric scientist from the University of Utah, and his team of researchers in the College of Engineering have made a remarkable discovery about how snowflakes respond to air turbulence during their fall.

Through their analysis of over half a million snowflakes and the development of novel instrumentation, they have revealed a surprisingly simple pattern underlying the movement of these delicate ice crystals.

Science behind snowflake movement

The speed at which snowflakes fall is of great interest in weather prediction and climate change research. According to Garrett, “How snowflakes fall has attracted a lot of interest for many decades because it is a critical parameter for predicting weather and climate change. This is related to the speed of the water cycle. How fast moisture falls out of the sky determines the lifetime of storms.”

Snowflakes, often referred to as “letters sent from heaven” by the renowned Japanese physicist Ukichiro Nakaya, contain valuable information about temperature and humidity fluctuations in the clouds. Although each snowflake is believed to be unique in its intricate structure, researchers have discovered patterns in how they move through the air.

The movement of snowflakes has far-reaching consequences beyond weather forecasting. It also affects climate change predictions, even in tropical regions.

Garrett explains, “Most precipitation starts as snow. The 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. It can even affect forecasts of a hurricane trajectory.”

Understanding the factors that influence snowflake movement is crucial for improving forecasts of precipitation distribution and the behavior of weather systems.

Measuring individual snowflakes accurately has been a long-standing challenge due to their low mass. Snowflakes often weigh around 10 micrograms, making high-precision measurements difficult.

To address this issue, Garrett collaborated with engineering faculty to develop the Differential Emissivity Imaging Disdrometer (DEID). This innovative instrument measures snowflakes’ hydrometeor mass, size, and density. The DEID has been successfully commercialized by Particle Flux Analytics, a company co-founded by Garrett, and is now deployed by the Utah Department of Transportation for avalanche forecasting.

A surprisingly simple pattern emerges

To study snowflake movement in natural environments, Garrett’s team conducted field experiments at Alta, a renowned ski destination and Utah’s snowiest place during the winter of 2020-21. They deployed the DEID alongside measurements of air temperature, relative humidity, and turbulence.

Additionally, a particle tracking system consisting of a laser light sheet and a single-lens reflex camera was set up to observe the movement of the snowflakes.

By analyzing the science and interaction between snowflakes and turbulence, while simultaneously measuring their mass, density, size, and observing their meandering paths, the researchers were able to obtain a comprehensive understanding of snowflake movement that was previously unavailable.

Contrary to expectations, the intricate shapes of snowflakes and their encounters with turbulent air did not result in unpredictable movements. Instead, the researchers discovered a surprisingly simple pattern. Snowflake acceleration was found to correlate with a parameter known as the Stokes number (St), which describes how quickly the particles respond to surrounding air movements.

Upon analyzing the acceleration of individual snowflakes, the researchers observed that the average acceleration increased nearly linearly with the Stokes number. Moreover, the distribution of these accelerations followed a single exponential curve that was independent of the Stokes number.

Snowflakes and atmospheric science mysteries

This mathematical pattern could also be connected to how changes in snowflake shapes and sizes influence their falling speed. It suggests a fundamental relationship between air movement and the transformation of snowflakes during their descent from the clouds.

Garrett reflects on this unexpected finding, stating, “That, to me, almost seems mystical. 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.”

Through meticulous analysis and the development of innovative instrumentation, the study led by Tim Garrett at the University of Utah has uncovered a surprisingly simple pattern in the movement of snowflakes. This research sheds light on the connection between air turbulence and the behavior of snowflakes during their descent.

In summary, these findings have important implications for weather forecasting, climate change predictions, and our understanding of atmospheric dynamics. As scientists continue to unravel the mysteries and science of snowflake formation and movement, we can expect further insights into the intricate processes occurring within our atmosphere.

The full study was published in the journal Physics of Fluids. The research received funding from the National Science Foundation, further highlighting the significance of this groundbreaking investigation.

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