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Analysis of the Atmosphere and the Ocean Upper Layer State Predictability for up to 5 Years Ahead Using the INMCM5 Climate Model Hindcasts

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Abstract

A series of hindcasts for 1–5 years were performed using the INM RAS climate model (INMCM5). Each forecast started on November 1 every year during 1980–2020. The predictability of large-scale climate variability modes on timescales from a season to 5 years is assessed with the series of INMCM5 hindcasts. The spatial distribution of correlation coefficients of the temporal anomalies of the annual mean ocean water temperature averaged for the depths from 0 to 300 m and correlation coefficients of temporal anomalies of the Arctic sea ice area are calculated using the hindcasts, historical experiments and their extensions according to the SSP3-7.0 scenario of the INM RAS climate model. The contributions of initial conditions and external forcings to the predictability of the anomaly correlation coefficients are evaluated.

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Authors and Affiliations

  1. Marchuk Institute of Numerical Mathematics, Russian Academy of Sciences, 119333, Moscow, Russia

    V. V. Vorobeva, E. M. Volodin, A. S. Gritsun & M. A. Tarasevich

  2. Hydrometeorological Research Center of the Russian Federation, 123242, Moscow, Russia

    V. V. Vorobeva & M. A. Tarasevich

  3. Obukhov Institute of Atmospheric Physics, Russian Academy of Sciences, 119017, Moscow, Russia

    V. V. Vorobeva & E. M. Volodin

  4. Moscow Institute of Physics and Technology, 141700, Dolgoprudny, Moscow oblast, Russia

    M. A. Tarasevich

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  1. V. V. Vorobeva
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Correspondence to V. V. Vorobeva.

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Translated from Meteorologiya i Gidrologiya, 2023, No. 7, pp. 36-47. https://doi.org/10.52002/0130-2906-2023-7-36-47.

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Vorobeva, V.V., Volodin, E.M., Gritsun, A.S. et al. Analysis of the Atmosphere and the Ocean Upper Layer State Predictability for up to 5 Years Ahead Using the INMCM5 Climate Model Hindcasts. Russ. Meteorol. Hydrol. 48, 581–589 (2023). https://doi.org/10.3103/S106837392307004X

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  • DOI: https://doi.org/10.3103/S106837392307004X

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