Improved Formulation of Fragmentation of Snow during Collisions with Graupel/Hail Based on Observations at Jungfraujoch: Cold Nondendritic Regime of Temperature

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Abstract
Much of the initiation of ice particles in deep precipitating clouds has been attributed to secondary ice production (SIP). Fragmentation during collisions among particles of ice precipitation is one of the known SIP processes. Some recent studies have used our theoretical formulation of this SIP process in the cloud microphysics scheme of numerical atmospheric models published in 2017. However, there has been a lack of observational data for better understanding of SIP processes. The focus of the present study is on fragmentation of naturally falling snowflakes during their collisions with graupel/hail particles, based on observations conducted at Jungfraujoch, a mountain pass in the Alps and located at about 3.6 km above mean sea level. The cloud top was from −25° to −32°C and cloud base at about −16°C. The study used a portable chamber specially designed to observe the fragmentation of snow particles outdoors. The detection threshold for counting fragments was about 0.2 mm. Fixed ice spheres in the chamber were used to mimic graupel or hail. Based on the observational study, we optimized the theoretical formulation for prediction of the number of fragments arising from collisions between snow and graupel/hail. The observations reveal an average number of fragments per collision of about 5. The study improved the prediction of SIP by this type of fragmentation compared to our original theoretical formulation, for snow consisting of mostly aggregates of crystals from the “nondendritic habit regime” of temperatures colder than −17°C. Significance Statement: This work advances knowledge about fragmentation of snow aloft, which is a process dominating the secondary ice production in natural clouds. Better empirical characterization of this process of initiation of cloud–ice particles allows its representation in atmospheric models, improving the quality of simulations.
Funding Information
  • Vetenskapsrådet (2021-05547)
  • VINNOVA (2020-03406)
  • Svenska Forskningsrådet Formas (2021-01463)