RadNet 1.0: exploring deep learning architectures for longwave radiative transfer

RadNet 1.0: exploring deep learning architectures for longwave radiative transfer

<p>Simulating global and regional climate at high resolution is essential to study the effects of climate change and capture extreme events affecting human populations. To achieve this goal, the scalability of climate models and efficiency of individual model components are both important. Rad...

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Bibliographic Details
Main Authors:	Y. Liu, R. Caballero, J. M. Monteiro
Format:	Article
Language:	English
Published:	Copernicus Publications 2020-09-01
Series:	Geoscientific Model Development
Online Access:	https://gmd.copernicus.org/articles/13/4399/2020/gmd-13-4399-2020.pdf

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