Data-driven Analysis and Learning of the Temporal Evolution of Ensemble Forecasts (B05)

• Subject Area: Image and Language Processing, Computer Graphics and Visualisation, Human Computer Interaction, Ubiquitous and Wearable Computing ; Computer Architecture, Embedded and Massively Parallel Systems
• Term: from 2015 to 2023
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 257899354

Our goal is to develop visualization techniques for nD multivariate 3D cloud ensembles, to analyse the dynamics of cloud formation and find specific relationships between model parameters and prognostic variables. To analyse the impact of clouds on local weather events we will shed light on data-driven approaches for simulating light transport in cloud ensembles. Another goal is the development of a testbed for deep learning of cloud formation processes. By using measured data and recorded forecasts from the past as training data, we will analyse whether a deep learning network can learn the non-linear relationships between forecasts and actual weather to improve a current forecast.

• DFG Programme: CRC/Transregios
• Subproject of: TRR 165: Waves to Weather
• Applicant Institution: Ludwig-Maximilians-Universität München
• Project Head: Professor Dr. Rüdiger Westermann