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A machine-learning approach to thunderstorm forecasting through post-processing of simulation data
April 29, 2024, 4:42 a.m. | Kianusch Vahid Yousefnia, Tobias B\"olle, Isabella Z\"obisch, Thomas Gerz
cs.LG updates on arXiv.org arxiv.org
Abstract: Thunderstorms pose a major hazard to society and economy, which calls for reliable thunderstorm forecasts. In this work, we introduce a Signature-based Approach of identifying Lightning Activity using MAchine learning (SALAMA), a feedforward neural network model for identifying thunderstorm occurrence in numerical weather prediction (NWP) data. The model is trained on convection-resolving ensemble forecasts over Central Europe and lightning observations. Given only a set of pixel-wise input parameters that are extracted from NWP data and …
abstract arxiv cs.lg data economy forecasting lightning machine machine learning major network neural network numerical numerical weather prediction physics.ao-ph post-processing prediction processing simulation society through type weather weather prediction work
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