Scientist at KIT’s Institute for Meteorology and Climate Research, exploring how deep learning can reveal and represent the complex dynamics of our planet.
Chatterjee, D., Schnitt, S., Bigalke, P., Acquistapace, C., & Crewell, S. (2024). Capturing the diversity of mesoscale trade wind cumuli using complementary approaches from self-supervised deep learning. Geophysical Research Letters, https://doi.org/10.1029/2024GL108889
Chatterjee, D., Acquistapace, C., Deneke, H., & Crewell, S. (2023). Understanding Cloud Systems’ Structure and Organization Using a Machine’s Self-Learning Approach. Artificial Intelligence for the Earth Systems, 2(4), e220096. https://doi.org/10.1175/AIES-D-22-0096.1
Crewell, S., Driemel, A., Phillips, J. M., & Chatterjee, D. (2024). Computational Geometry of Earth System Analysis (Dagstuhl Seminar 23342). Dagstuhl Reports, 13(8), 91-105. Schloss Dagstuhl – Leibniz-Zentrum für Informatik. https://doi.org/10.4230/DagRep.13.8.91
Minghze, L., Chatterjee, D., Glassmeier, F., Senf, F., & Wang, B., (2025). Tracking Low-Level Cloud Systems with Topology. IEEE Workshop on Topological Data Analysis and Visualization (TopoInVis), Vienna, Austria, 2025, pp. 89-99, doi: 10.1109/TopoInVis68599.2025.00013.
Acquistapace, C., Schnitt, S., Krause, S., Risse, N., Lange, D., Chatterjee, D. (2025). Characterization of precipitation life cycle in the trades across different regimes of shallow convection. Quarterly Journal of the Royal Meteorological Society. https://doi.org/10.1002/qj.70038
Chatterjee, D., Raabe, N., & Crewell, S. (2025). Four Low-Level Cloud Regimes Revealed by Latent Space Analysis and Their Impact on Solar Energy Variability, Journal of Machine Learning: Earth, https://doi.org/10.1088/3049-4753/ae4e30
🔄 Under Review
Netz, L., Chatterjee, D., Fiolleau, T., Remy, R., Acquistapache, C., Continuous mapping of deep convective cores from geostationary infrared imagery using a multi-scale composite-loss conditional GAN trained on GPM-DPR. (Submitted to AIES)
Chatterjee, D., Raabe, N., Knippertz, P., Crewell, S., Dueben, P., Vanniere, B., A New Concept for Comparing Satellite Observations and km-Scale Atmospheric Simulations using Self-Supervised Machine Learning. (to be submitted to JAMES, in preparation)
Chatterjee, D., Raabe, N., Knippertz, P., Crewell, S., Dueben, P., Vanniere, B., Diagnosing Cloud Evolution Biases in km-Scale Models Using Latent-Space Dynamics. (to be submitted to AIES, in preparation)
