Snowflake Motion Study Enhances Rainfall Forecasts

New research reveals how the movement of snowflakes can improve weather predictions by analyzing their unique falling patterns.

Scientists used 3D-printed snowflakes to study their descent in a water-glycerine mixture, simulating atmospheric conditions.
The study identified four distinct falling patterns: stable, zigzag, transitional, and spiraling, affecting precipitation formation.
Complex snowflake shapes tend to fall more stably, while simpler shapes are prone to instability and greater sideways movement.
Understanding snowflake movement can help meteorologists interpret radar signals more accurately, improving rain and snow forecasts.
The research also offers insights into cloud reflectivity and the potential for enhanced climate models and long-term weather predictions.