Kevin Ohneiser, Patric Seifert, Willi Schimmel, Fabian Senf, Tom Gaudek, Martin Radenz, Audrey Teisseire, Veronika Ettrichrätz, Teresa Vogl, Nina Maherndl, Nils Pfeifer, Jan Henneberger, Anna J. Miller, Nadja Omanovic, Christopher Fuchs, Huiying Zhang, Fabiola Ramelli, Robert Spirig, Anton Kötsche, Heike Kalesse-Los, Maximilian Maahn, Heather Corden, Alexis Berne, Majid Hajipour, Hannes Griesche, Julian Hofer, Ronny Engelmann, Annett Skupin, Albert Ansmann, Holger Baars
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 January 2024 observed over the Swiss Plateau in Switzerland. This 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 ice mass was rimed, which is attributed to persistent coexistence of falling ice crystals and supercooled water within low-level supercooled liquid water layers. Interaction of seeder and feeder clouds results in a significant precipitation enhancement. This has implications on the water cycle. From the anti-correlation between surface precipitation and liquid water path we estimated that 20 %–40 % of the precipitation stems from the feeder cloud. However, we have to note that the value of 20 %–40 % is strongly dependent on the assumed reproduction rate of liquid water in the feeder cloud. 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 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 improved understanding of seeder-feeder interactions can contribute to enhancing weather forecast models, particularly in regions affected by persistent low-level supercooled stratus clouds.