atmospheric water cycle: clouds, precipitation, water vapor
ground-, ship-, air- and space-borne passive and active remote sensing
GRaWAC: G-band Radar for Water vapor and Arctic Clouds
synergistic retrieval development
machine learning approaches for retrievals and imagery
Current Projects
(AC)3: Climate Relevant Atmospheric and Surface Processes and Feedback Mechanisms (DFG); sub-project E03
Syncloud-G: Synergistic observations of clouds, water vapor and precipitation using multi-frequency G-band radars at AWIPEV station, Ny-Alesund, Svalbard
Schnitt, S., Mech, M., Goliasch, J., Rose, T., and Crewell, S.: G-band Radar for Water vapor and Arctic Clouds (GRaWAC): novel insights on Arctic water vapor, clouds and precipitation, EGUsphere, 1-29, doi.org/10.5194/egusphere-2025-5563, 2025
Acquistapace, C., Schnitt, S., Krause, S., Risse, N., Lange, D., and Chatterjee, D.: Characterizing trade wind shallow convective regimes at open sea with a synergy of ship-based vertical profiling observations. Quarterly Journal of the Royal Meteorological Society, e70038, doi.org/10.1002/qj.70038, 2025
Ehrlich, A., and Coauthors (incl S. Schnitt), 2024: A comprehensive in-situ and remote sensing data set collected during the HALO–(AC)³ aircraft campaign. Earth System Science Data Discussions, doi.org/10.5194/essd-2024-280
Wendisch, M. and Coauthors (incl S. Schnitt), 2024: Overview: Quasi-Lagrangian observations of Arctic air mass transformations – Introduction and initital results of the HALO-AC3 aircraft campaign. Atmospheric Chemistry and Physics, 24 (15), 8865-8892, doi.org/10.5194/acp-24-8865-2024
Schirmacher, I., S. Schnitt, M. Klingebiel, N. Maherndl, B. Kirbus, A. Ehrlich, M. Mech, S. Crewell, 2024: Clouds and precipitation in the initial phase of marine cold air outbreaks as observed by airborne remote sensing, Atmospheric Measurement Techniques, 12823-12842, doi.org/10.5194/acp-24-12823-2024
Chatterjee, D., S. Schnitt, P. Bigalke, C. Acquistapace, and S. Crewell, 2024: Capturing the diversity of mesoscale trade wind cumuli using complementary approaches from self-supervised deep learning. Geophysical Research Letters, 51,e2024GL108889, doi.org/10.1029/2024GL108889
Schnitt, S., A. Foth, H. Kalesse-Los, M. Mech, C. Acquistapace, F. Jansen, U. Löhnert, B. Pospichal, J. Röttenbacher, S. Crewell, B. Stevens, 2024: Ground- and ship-based microwave radiometer measurements during EUREC4A. Earth System Science Data, doi.org/10.5194//essd-16-681-2024
Lamer, K., P. Kollias, V. Amiridis, E. Marinou, U. Loehnert, S. Schnitt and A. McComiskey, 2023: Ground-Based Remote-Sensing of Key Properties. In Fast Processes in Large-Scale Atmospheric Models (eds Y. Liu and P. Kollias), doi.org/10.1002/9781119529019.ch14
Schnitt, S., Löhnert, U., Preusker, R., 2020: Potential of Dual-Frequency Radar and Microwave Radiometer Synergy for Water Vapor Profiling in the Cloudy Trade Wind Environment, Journal of Atmospheric and Oceanic Technology, 37(11), 1973-1986, doi.org/10.1175/JTECH-D-19-0110.1
Stevens, B. et al. (incl S. Schnitt), 2020: The Added Value of Large-eddy and Storm-resolving Models for Simulating Clouds and Precipitation, Journal of the Meteorological Society of Japan. Ser. II, 98(2), 395-435, doi.org/10.2151/jmsj.2020-021
Schnitt, S., Orlandi, E., Mech, M., Ehrlich, A., Crewell, S., 2017: Characterization of Water Vapor and Clouds During the Next-Generation Aircraft Remote Sensing for Validation (NARVAL) South Studies, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10(7), 3114-3124, doi.org/10.1109/JSTARS.2017.2687943
Education
PhD (Meteorology): Advancing Ground-Based Water Vapor Profiling through Synergy of Microwave Radiometer and Dual-Frequency Radar, University of Cologne (2020) link
M.Sc. (Physics): Evaluation of trade wind cloud properties using a passive airborne microwave radiometer during the NARVAL campaign, Universität zu Köln (2016)
uni-koeln.de