Forecasting dryland vegetation condition months in advance through satellite data assimilation

Forecasting drought and its impact on agriculture and ecosystems is challenged by a lack of knowledge of vegetation access to deep moisture. Here the authors show that combining vegetation and water storage remote sensing can be used to infer this knowledge, allowing drought impact forecasts months...

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Autores principales:	Siyuan Tian, Albert I. J. M. Van Dijk, Paul Tregoning, Luigi J. Renzullo
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2019
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/afb25d8b12f44b40b62f2fe858714565
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id	oai:doaj.org-article:afb25d8b12f44b40b62f2fe858714565
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spelling	oai:doaj.org-article:afb25d8b12f44b40b62f2fe8587145652021-12-02T16:57:31ZForecasting dryland vegetation condition months in advance through satellite data assimilation10.1038/s41467-019-08403-x2041-1723https://doaj.org/article/afb25d8b12f44b40b62f2fe8587145652019-01-01T00:00:00Zhttps://doi.org/10.1038/s41467-019-08403-xhttps://doaj.org/toc/2041-1723Forecasting drought and its impact on agriculture and ecosystems is challenged by a lack of knowledge of vegetation access to deep moisture. Here the authors show that combining vegetation and water storage remote sensing can be used to infer this knowledge, allowing drought impact forecasts months in advance.Siyuan TianAlbert I. J. M. Van DijkPaul TregoningLuigi J. RenzulloNature PortfolioarticleScienceQENNature Communications, Vol 10, Iss 1, Pp 1-7 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Siyuan Tian Albert I. J. M. Van Dijk Paul Tregoning Luigi J. Renzullo Forecasting dryland vegetation condition months in advance through satellite data assimilation
description	Forecasting drought and its impact on agriculture and ecosystems is challenged by a lack of knowledge of vegetation access to deep moisture. Here the authors show that combining vegetation and water storage remote sensing can be used to infer this knowledge, allowing drought impact forecasts months in advance.
format	article
author	Siyuan Tian Albert I. J. M. Van Dijk Paul Tregoning Luigi J. Renzullo
author_facet	Siyuan Tian Albert I. J. M. Van Dijk Paul Tregoning Luigi J. Renzullo
author_sort	Siyuan Tian
title	Forecasting dryland vegetation condition months in advance through satellite data assimilation
title_short	Forecasting dryland vegetation condition months in advance through satellite data assimilation
title_full	Forecasting dryland vegetation condition months in advance through satellite data assimilation
title_fullStr	Forecasting dryland vegetation condition months in advance through satellite data assimilation
title_full_unstemmed	Forecasting dryland vegetation condition months in advance through satellite data assimilation
title_sort	forecasting dryland vegetation condition months in advance through satellite data assimilation
publisher	Nature Portfolio
publishDate	2019
url	https://doaj.org/article/afb25d8b12f44b40b62f2fe858714565
work_keys_str_mv	AT siyuantian forecastingdrylandvegetationconditionmonthsinadvancethroughsatellitedataassimilation AT albertijmvandijk forecastingdrylandvegetationconditionmonthsinadvancethroughsatellitedataassimilation AT paultregoning forecastingdrylandvegetationconditionmonthsinadvancethroughsatellitedataassimilation AT luigijrenzullo forecastingdrylandvegetationconditionmonthsinadvancethroughsatellitedataassimilation
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Forecasting dryland vegetation condition months in advance through satellite data assimilation

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