NOWCASTING USING GENERATIVE NEURAL NETWORKS

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for precipitation nowcasting using generative neural networks. One of the methods includes obtaining a context temporal sequence of a plurality of context radar fields characterizing a real-world location...

Full description

Saved in:
Bibliographic Details
Main Authors MIROWSKI, Piotr Wojciech, BROCK, Andrew, LENC, Karel, RAVURI, Suman, LAM, Remi Roger Alain Paul, WILLSON, Matthew James
Format Patent
LanguageEnglish
French
German
Published 11.10.2023
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
CONTROLLING
COUNTING
MEASURING
METEOROLOGY
PHYSICS
REGULATING
SIGNALLING
SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
TESTING
TRAFFIC CONTROL SYSTEMS
Online AccessGet full text

Cover

More Information
Summary:Methods, systems, and apparatus, including computer programs encoded on computer storage media, for precipitation nowcasting using generative neural networks. One of the methods includes obtaining a context temporal sequence of a plurality of context radar fields characterizing a real-world location, each context radar field characterizing the weather in the real-world location at a corresponding preceding time point; sampling a set of one or more latent inputs by sampling values from a specified distribution; and for each sampled latent input, processing the context temporal sequence of radar fields and the sampled latent input using a generative neural network that has been configured through training to process the temporal sequence of radar fields to generate as output a predicted temporal sequence comprising a plurality of predicted radar fields, each predicted radar field in the predicted temporal sequence characterizing the predicted weather in the real-world location at a corresponding future time point.
Bibliography:Application Number: EP20220710509