Impact of seeder-feeder cloud interaction on precipitation formation: a case study based on extensive remote-sensing, in-situ and model data

Abstract. A comprehensive approach to study the seeder-feeder mechanism in unprecedented detail from a combined remote-sensing, in-situ, and model perspective is shown. This publication aims at investigating the role of the interplay of a seeder-feeder cloud system and its influence on precipitation formation based on a case study from 8 Jan 2024 observed over the Swiss Plateau in Switzerland.

The case study offers an ideal setup for applying several advanced remote-sensing techniques and retrieval algorithms, including fall streak tracking, radar Doppler peak separation, dual-wavelength radar applications, a liquid detection retrieval, a riming retrieval, and an ice crystals shape retrieval. Results indicate that a large portion of the ice mass was rimed, which is attributed to the persistent coexistence of falling ice crystals and supercooled water within low-level supercooled liquid water layers. The interaction of the seeder and feeder clouds results in a significant precipitation enhancement. This has implications on the water cycle. It is also found that precipitation was significantly underestimated by the operational ICON-D2 model runs during the seeder-feeder process. Contrarily, during periods when the cloud system does not interact, the precipitation is significantly overestimated by the model.

This study aims at giving an overview from a remote-sensing, in-situ and model perspective on a seeder-feeder event in an unprecedented detail by exploiting a big set of retrievals applicable to big remote-sensing and in situ data. Utilizing different retrievals gives a consistent view on the seeder-feeder case study which is an important basis for future studies. It is demonstrated how the improved understanding of seeder-feeder interactions can contribute to enhancing weather forecast models, particularly in regions affected by persistent low-level supercooled stratus clouds.