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Neural Network–Based Precipitable Water Vapor Estimation Integrating Ground Observations and GFS Data

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Bibliographic Details
Published in:Advances in Meteorology
Format: Online Article RSS Article
Published: 2026
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container_title Advances in Meteorology
description
discipline_display Meteorology
discipline_facet Meteorology
format Online Article
RSS Article
genre Journal Article
id rss_article:62238
institution FRELIP
journal_source_facet Advances in Meteorology
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle Neural Network–Based Precipitable Water Vapor Estimation Integrating Ground Observations and GFS Data
Meteorology
General
Meteorology
sub_discipline_display General
sub_discipline_facet General
subject_display Meteorology
General
Meteorology
Meteorology
General
Meteorology
subject_facet Meteorology
General
Meteorology
title Neural Network–Based Precipitable Water Vapor Estimation Integrating Ground Observations and GFS Data
title_auth Neural Network–Based Precipitable Water Vapor Estimation Integrating Ground Observations and GFS Data
title_full Neural Network–Based Precipitable Water Vapor Estimation Integrating Ground Observations and GFS Data
title_fullStr Neural Network–Based Precipitable Water Vapor Estimation Integrating Ground Observations and GFS Data
title_full_unstemmed Neural Network–Based Precipitable Water Vapor Estimation Integrating Ground Observations and GFS Data
title_short Neural Network–Based Precipitable Water Vapor Estimation Integrating Ground Observations and GFS Data
title_sort neural network–based precipitable water vapor estimation integrating ground observations and gfs data
topic Meteorology
General
Meteorology
url https://www.hindawi.com/journals/amete/2026/3554425/