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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Cited articles

Ayzel, G., Scheffer, T., and Heistermann, M.: RainNet v1.0: a convolutional neural network for radar-based precipitation nowcasting, Geosci. Model Dev., 13, 2631–2644, https://doi.org/10.5194/gmd-13-2631-2020, 2020. a, b
Baumgart, M., Riemer, M., Wirth, V., Teubler, F., and Lang, S. T.: Potential vorticity dynamics of Forecast errors: A quantitative case study, Mon. Weather Rev., 146, 1405–1425, https://doi.org/10.1175/MWR-D-17-0196.1, 2018. a
Berman, J. D. and Torn, R. D.: The impact of initial condition and warm conveyor belt forecast uncertainty on variability in the downstream waveguide in an ECWMF case study, Mon. Weather Rev., 147, 4071–4089, https://doi.org/10.1175/MWR-D-18-0333.1, 2019. a
Binder, H., Boettcher, M., Joos, H., and Wernli, H.: The role of warm conveyor belts for the intensification of extratropical cyclones in Northern Hemisphere winter, J. Atmos. Sci., 73, 3997–4020, https://doi.org/10.1175/JAS-D-15-0302.1, 2016. a, b
Bosart, L. F., Moore, B. J., Cordeira, J. M., Archambault, H. M., Bosart, L. F., Moore, B. J., Cordeira, J. M., and Archambault, H. M.: Interactions of North Pacific tropical, midlatitude, and polar disturbances resulting in linked extreme weather events over North America in October 2007, Mon. Weather Rev., 145, 1245–1273, https://doi.org/10.1175/MWR-D-16-0230.1, 2017. a
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.