Improving weather forecasting by assimilation of water vapor isotopes

Abstract Stable water isotopes, which depend on meteorology and terrain, are important indicators of global water circulation. During the past 10 years, major advances have been made in general circulation models that include water isotopes, and the understanding of water isotopes has greatly progre...

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Autores principales:	Masataka Tada, Kei Yoshimura, Kinya Toride
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/f17dcfd2455540a5b581cf53f73c22d8
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spelling	oai:doaj.org-article:f17dcfd2455540a5b581cf53f73c22d82021-12-02T17:23:47ZImproving weather forecasting by assimilation of water vapor isotopes10.1038/s41598-021-97476-02045-2322https://doaj.org/article/f17dcfd2455540a5b581cf53f73c22d82021-09-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-97476-0https://doaj.org/toc/2045-2322Abstract Stable water isotopes, which depend on meteorology and terrain, are important indicators of global water circulation. During the past 10 years, major advances have been made in general circulation models that include water isotopes, and the understanding of water isotopes has greatly progressed as a result of innovative, improved observation techniques. However, no previous studies have combined modeled and observed isotopes using data assimilation, nor have they investigated the impacts of real observations of isotopes. This is the first study to assimilate real satellite observations of isotopes using a general circulation model, then investigate the impacts on global dynamics and local phenomena. The results showed that assimilating isotope data improved not only the water isotope field but also meteorological variables such as air temperature and wind speed. Furthermore, the forecast skills of these variables were improved by a few percent, compared with a model that did not assimilate isotope observations.Masataka TadaKei YoshimuraKinya TorideNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-9 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Masataka Tada Kei Yoshimura Kinya Toride Improving weather forecasting by assimilation of water vapor isotopes
description	Abstract Stable water isotopes, which depend on meteorology and terrain, are important indicators of global water circulation. During the past 10 years, major advances have been made in general circulation models that include water isotopes, and the understanding of water isotopes has greatly progressed as a result of innovative, improved observation techniques. However, no previous studies have combined modeled and observed isotopes using data assimilation, nor have they investigated the impacts of real observations of isotopes. This is the first study to assimilate real satellite observations of isotopes using a general circulation model, then investigate the impacts on global dynamics and local phenomena. The results showed that assimilating isotope data improved not only the water isotope field but also meteorological variables such as air temperature and wind speed. Furthermore, the forecast skills of these variables were improved by a few percent, compared with a model that did not assimilate isotope observations.
format	article
author	Masataka Tada Kei Yoshimura Kinya Toride
author_facet	Masataka Tada Kei Yoshimura Kinya Toride
author_sort	Masataka Tada
title	Improving weather forecasting by assimilation of water vapor isotopes
title_short	Improving weather forecasting by assimilation of water vapor isotopes
title_full	Improving weather forecasting by assimilation of water vapor isotopes
title_fullStr	Improving weather forecasting by assimilation of water vapor isotopes
title_full_unstemmed	Improving weather forecasting by assimilation of water vapor isotopes
title_sort	improving weather forecasting by assimilation of water vapor isotopes
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/f17dcfd2455540a5b581cf53f73c22d8
work_keys_str_mv	AT masatakatada improvingweatherforecastingbyassimilationofwatervaporisotopes AT keiyoshimura improvingweatherforecastingbyassimilationofwatervaporisotopes AT kinyatoride improvingweatherforecastingbyassimilationofwatervaporisotopes
_version_	1718381003154653184

Improving weather forecasting by assimilation of water vapor isotopes

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