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A Physics-informed Deep Learning Based Clustering to Investigate the Impact of Regional European Radiative Forcing on Arctic Climate and Upper Atmospheric Dynamics

S. Mehrdad, D. Handorf, I. Höschel, K. Karami, J. Quaas, S. Dipu, and C. Jacobi. (2024)

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ALAS: Active Learning for Autoconversion Rates Prediction from Satellite DataM. Novitasari, J. Quaas, and M. Rodrigues. (2024)Arctic climate response to European radiative forcing: a deep learning study on circulation pattern changesS. Mehrdad, D. Handorf, I. Höschel, K. Karami, J. Quaas, S. Dipu, and C. Jacobi. Weather and Climate Dynamics, 5 (4): 1223-1268 (2024)Arctic Climate Response to European Radiative Forcing: A Deep Learning ApproachS. Mehrdad, D. Handorf, I. Höschel, K. Karami, J. Quaas, S. Dipu, and C. Jacobi. EGUsphere, (2024)A belowground perspective on the nexus between biodiversity change, climate change, and human well-beingN. Eisenhauer, K. Frank, A. Weigelt, B. Bartkowski, R. Beugnon, K. Liebal, M. Mahecha, M. Quaas, D. Al-Halbouni, A. Bastos and 38 other author(s). Journal of Sustainable Agriculture and Environment, 3 (2): e212108 (2024)Optimizing Kilometer-Scale Climate Modeling: Refining Cloud Microphysics Using Machine Learning and Satellite CorrelationH. Eichholz, J. Kretzschmar, J. Umlauft, and J. Quaas. Copernicus Meetings, (2024)Towards machine-learning calibration of cloud parameters in the kilometre-resolution ICON atmosphere modelH. Eichholz, J. Kretzschmar, D. Watson-Parris, J. Umlauft, and J. Quaas. EGU General Assembly Conference Abstracts, page EGU--5003. (2023)Leveraging surface observations and passive satellite retrievals of cloud properties: Applications to cloud type classification and cloud base height retrievalJ. Lenhardt, J. Quaas, D. Sejdinovic, and D. Klocke. (2024)CloudViT: classifying cloud types in global satellite data and in kilometre-resolution simulations using vision transformersJ. Lenhardt, J. Quaas, D. Sejdinovic, and D. Klocke. EGUsphere, (2024)Cloudy with a chance of precision: satellite’s autoconversion rates forecasting powered by machine learningM. Novitasari, J. Quaas, and M. Rodrigues. Environmental Data Science, (2024)ALAS: Active Learning for Autoconversion Rates Prediction from Satellite DataM. Novitasari, J. Quaas, and M. Rodrigues. NeurIPS 2023 AI for Science Workshop, (2023)

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