Graphical Abstract

Kudo, A., 2022: Statistical post-processing for gridded temperature prediction using encoder‒decoder-based deep convolutional neural networks. J. Meteor. Soc. Japan, 100,
https://doi.org/10.2151/jmsj.2022-011
Graphical Abstract NEW GA

 

Plain Language Summary: In this study, an encoder‒decoder-based convolutional neural network (CNN) has been proposed to predict gridded temperatures at the surface around the Kanto region in Japan. Verification results showed that the proposed model greatly improves the Japan Meteorological Agency's (JMA's) operational gridded temperature guidance and can correct NWP model biases, such as a positional error of coastal fronts (Fig. 1) and extreme temperatures.

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