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Tellus A: Dynamic Meteorology and Oceanography Volume 68, 2016 - Issue 1
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Data assimilation and predictability

AMSR2 all-sky radiance assimilation and its impact on the analysis and forecast of Hurricane Sandy with a limited-area data assimilation system

Chun YangKey Laboratory of Meteorological Disaster of Ministry of Education (KLME)/Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological DisasterNanjing University of Information Science & Technology, Nanjing, China;National Center for Atmospheric ResearchBoulder, CO, USA
,
Zhiquan LiuNational Center for Atmospheric ResearchBoulder, CO, USACorrespondence[email protected]
,
Jamie BreschNational Center for Atmospheric ResearchBoulder, CO, USA
,
Syed R. H. RizviNational Center for Atmospheric ResearchBoulder, CO, USA
,
Xiang-Yu HuangCentre for Climate Research Singapore, Singapore, Singapore
&
Jinzhong MinKey Laboratory of Meteorological Disaster of Ministry of Education (KLME)/Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological DisasterNanjing University of Information Science & Technology, Nanjing, China
Article: 30917 | Received 06 Jan 2016, Accepted 06 May 2016, Published online: 01 Jun 2016

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Akhilesh S. Nair, Rohit Mangla, Thiruvengadam P & J. Indu. (2022) Remote sensing data assimilation. Hydrological Sciences Journal 67:16, pages 2457-2489.
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