Can Machines Learn to Predict Weather? Using Deep Learning to Predict Gridded 500‐hPa Geopotential Height From Historical Weather Data

Can Machines Learn to Predict Weather? Using Deep Learning to Predict Gridded 500‐hPa Geopotential Height From Historical Weather Data

Abstract We develop elementary weather prediction models using deep convolutional neural networks (CNNs) trained on past weather data to forecast one or two fundamental meteorological fields on a Northern Hemisphere grid with no explicit knowledge about physical processes. At forecast lead times up...

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Bibliographic Details
Main Authors: Jonathan A. Weyn, Dale R. Durran, Rich Caruana
Format: Article
Language:English
Published: American Geophysical Union (AGU) 2019-08-01
Series:Journal of Advances in Modeling Earth Systems
Subjects:
machine learning
weather prediction
deep learning
neural network
Online Access:https://doi.org/10.1029/2019MS001705

Internet

https://doi.org/10.1029/2019MS001705

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