Articles | Volume 15, issue 2
https://doi.org/10.5194/gmd-15-715-2022
https://doi.org/10.5194/gmd-15-715-2022
Model description paper
 | 
27 Jan 2022
Model description paper |  | 27 Jan 2022

EuLerian Identification of ascending AirStreams (ELIAS 2.0) in numerical weather prediction and climate models – Part 1: Development of deep learning model

Julian F. Quinting and Christian M. Grams

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Short summary
Physical processes in weather systems importantly affect the midlatitude large-scale circulation. This study introduces an artificial-intelligence-based framework which allows the identification of an important weather system – the so-called warm conveyor belt (WCB) – at comparably low computational costs and from data at low spatial and temporal resolution. The framework thus newly enables the systematic investigation of WCBs in large data sets such as climate model projections.