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Tellus A: Dynamic Meteorology and Oceanography Volume 72, 2020 - Issue 1

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Research Article

Dynamically weighted hybrid gain data assimilation: perfect model testing

Helena Barbieri De Azevedo1 Instituto Nacional de Pesquisas Espaciais, Cachoeira Paulista, SP, BrazilCorrespondence[email protected]

Luis Gustavo Gonçalves De Gonçalves1 Instituto Nacional de Pesquisas Espaciais, Cachoeira Paulista, SP, Brazil

Eugenia Kalnay2 University of Maryland, College Park, MD, USA

Matthew Wespetal2 University of Maryland, College Park, MD, USA

Pages 1-11 | Received 03 Oct 2019, Accepted 06 Oct 2020, Published online: 13 Nov 2020

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https://doi.org/10.1080/16000870.2020.1835310
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Citations (3)

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Articles from other publishers (3)

Georgy I. Shapiro & Mohammed Salim. (2023) How Efficient Is Model-to-Model Data Assimilation at Mitigating Atmospheric Forcing Errors in a Regional Ocean Model?. Journal of Marine Science and Engineering 11:5, pages 935.
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Ivette H. Banos, Will D. Mayfield, Guoqing Ge, Luiz F. Sapucci, Jacob R. Carley & Louisa Nance. (2022) Assessment of the data assimilation framework for the Rapid Refresh Forecast System v0.1 and impacts on forecasts of a convective storm case study. Geoscientific Model Development 15:17, pages 6891-6917.
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Chih-Chien Chang, Shu-Chih Yang & Stephen G. Penny. (2022) A Regional Hybrid Gain Data Assimilation System and Preliminary Evaluation Based on Radio Occultation Reflectivity Assimilation. SOLA 18:0, pages 33-40.
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