Articles | Volume 15, issue 23
Model experiment description paper
13 Dec 2022
Model experiment description paper |  | 13 Dec 2022

Temperature forecasting by deep learning methods

Bing Gong, Michael Langguth, Yan Ji, Amirpasha Mozaffari, Scarlet Stadtler, Karim Mache, and Martin G. Schultz

Data sets

2m Temperature Forecast by Deep Learning Gong, Bing; Langguth, Michael; Ji, Yan; Mozaffari, Amirpasha; Stadtler, Scarlet; Mache, Karim; Schultz, Martin G.

Model code and software

Atmospheric Machine Learning Benchmarking System Gong, Bing; Langguth, Michael; Ji, Yan

Short summary
Inspired by the success of deep learning in various domains, we test the applicability of video prediction methods by generative adversarial network (GAN)-based deep learning to predict the 2 m temperature over Europe. Our video prediction models have skill in predicting the diurnal cycle of 2 m temperature up to 12 h ahead. Complemented by probing the relevance of several model parameters, this study confirms the potential of deep learning in meteorological forecasting applications.