The Atmosphere, Ocean and Sea Ice Coupled Model for Medium-range Weather Prediction.

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Title: The Atmosphere, Ocean and Sea Ice Coupled Model for Medium-range Weather Prediction.
Authors: Fadeev, R. Yu.1,2,3 (AUTHOR) rost.fadeev@gmail.com, Resnyanskii, Yu. D.2 (AUTHOR), Strukov, B. S.2 (AUTHOR), Zelenko, A. A.2 (AUTHOR), Mizyak, V. G.2 (AUTHOR), Tolstykh, M. A.1,2,3 (AUTHOR)
Source: Russian Meteorology & Hydrology. Jun2025, Vol. 50 Issue 6, p507-516. 10p.
Subject Terms: *Atmosphere, *Weather forecasting, *Seawater, *Atmospheric models, *Sea ice, *Data assimilation, *Ocean-atmosphere interaction
Abstract: The paper discusses the methodology of initial data generation for SLNE coupled model components. The SLNE model includes the coupled SLAV atmosphere, NEMO ocean and SI3 sea ice models. The article also presents the results of studying medium-range weather prediction skill of the SLNE in comparison with the SLAV072L96 operational technology of the Hydrometeorological Research Center of Russia. It is shown that the coupled model, starting from assimilated atmosphere and ocean data, is slightly inferior in forecast accuracy with respect to the SLAV072L96 model. This indicates that further work is needed to improve the consistency of initial atmosphere and oceanic states. [ABSTRACT FROM AUTHOR]
Database: Energy & Power Source
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Abstract:The paper discusses the methodology of initial data generation for SLNE coupled model components. The SLNE model includes the coupled SLAV atmosphere, NEMO ocean and SI3 sea ice models. The article also presents the results of studying medium-range weather prediction skill of the SLNE in comparison with the SLAV072L96 operational technology of the Hydrometeorological Research Center of Russia. It is shown that the coupled model, starting from assimilated atmosphere and ocean data, is slightly inferior in forecast accuracy with respect to the SLAV072L96 model. This indicates that further work is needed to improve the consistency of initial atmosphere and oceanic states. [ABSTRACT FROM AUTHOR]
ISSN:10683739
DOI:10.3103/S1068373925060068