Evaluation of the INM RAS climate model skill in climate indices and stratospheric anomalies on seasonal timescale

The study of winter seasonal predictability with the climate model INM-CM5-0 is presented. Initial conditions were produced using ERA-Interim reanalysis data for atmosphere, SODA3.4.2 reanalysis data for ocean and the bias-correction algorithm. The seasonal 5-month re-forecasts consisting of 10 ense...

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Autores principales:	Vasilisa Vorobyeva, Evgeny Volodin
Formato:	article
Lenguaje:	EN
Publicado:	Taylor & Francis Group 2021
Materias:	seasonal forecast nao pna stratosphere correlation Oceanography GC1-1581 Meteorology. Climatology QC851-999
Acceso en línea:	https://doaj.org/article/6734debdec6241468e3308130f61b642
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spelling	oai:doaj.org-article:6734debdec6241468e3308130f61b6422021-12-01T14:40:58ZEvaluation of the INM RAS climate model skill in climate indices and stratospheric anomalies on seasonal timescale1600-087010.1080/16000870.2021.1892435https://doaj.org/article/6734debdec6241468e3308130f61b6422021-01-01T00:00:00Zhttp://dx.doi.org/10.1080/16000870.2021.1892435https://doaj.org/toc/1600-0870The study of winter seasonal predictability with the climate model INM-CM5-0 is presented. Initial conditions were produced using ERA-Interim reanalysis data for atmosphere, SODA3.4.2 reanalysis data for ocean and the bias-correction algorithm. The seasonal 5-month re-forecasts consisting of 10 ensemble members with small initial condition perturbations for each year over the 35-yr period are conducted. A comparison of the multiyear mean winter averaged anomaly correlation for basic variables in several regions with similar results of SLAV model was conducted. An increase in the anomaly correlation for the years with El Niño and La Niña events was shown. The predictability of NAO and PNA indices was studied. INM-CM5-0 provides very high skill in predicting the winter NAO (correlation coefficient of 0.71 with ERA-Interim reanalysis and 0.68 with instrumental CRU data for 1991–2010). It was shown, that the stratospheric variability provides a significant contribution, although potentially is not the only cause of model high skill in NAO index predictability. Correlation coefficients for PNA index in December-February is 0.60. In the years of the most pronounced El Niño the values of PNA index have significantly positive values, and for La Niña years they are noticeably less than zero.Vasilisa VorobyevaEvgeny VolodinTaylor & Francis Grouparticleseasonal forecastnaopnastratospherecorrelationOceanographyGC1-1581Meteorology. ClimatologyQC851-999ENTellus: Series A, Dynamic Meteorology and Oceanography, Vol 73, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	seasonal forecast nao pna stratosphere correlation Oceanography GC1-1581 Meteorology. Climatology QC851-999
spellingShingle	seasonal forecast nao pna stratosphere correlation Oceanography GC1-1581 Meteorology. Climatology QC851-999 Vasilisa Vorobyeva Evgeny Volodin Evaluation of the INM RAS climate model skill in climate indices and stratospheric anomalies on seasonal timescale
description	The study of winter seasonal predictability with the climate model INM-CM5-0 is presented. Initial conditions were produced using ERA-Interim reanalysis data for atmosphere, SODA3.4.2 reanalysis data for ocean and the bias-correction algorithm. The seasonal 5-month re-forecasts consisting of 10 ensemble members with small initial condition perturbations for each year over the 35-yr period are conducted. A comparison of the multiyear mean winter averaged anomaly correlation for basic variables in several regions with similar results of SLAV model was conducted. An increase in the anomaly correlation for the years with El Niño and La Niña events was shown. The predictability of NAO and PNA indices was studied. INM-CM5-0 provides very high skill in predicting the winter NAO (correlation coefficient of 0.71 with ERA-Interim reanalysis and 0.68 with instrumental CRU data for 1991–2010). It was shown, that the stratospheric variability provides a significant contribution, although potentially is not the only cause of model high skill in NAO index predictability. Correlation coefficients for PNA index in December-February is 0.60. In the years of the most pronounced El Niño the values of PNA index have significantly positive values, and for La Niña years they are noticeably less than zero.
format	article
author	Vasilisa Vorobyeva Evgeny Volodin
author_facet	Vasilisa Vorobyeva Evgeny Volodin
author_sort	Vasilisa Vorobyeva
title	Evaluation of the INM RAS climate model skill in climate indices and stratospheric anomalies on seasonal timescale
title_short	Evaluation of the INM RAS climate model skill in climate indices and stratospheric anomalies on seasonal timescale
title_full	Evaluation of the INM RAS climate model skill in climate indices and stratospheric anomalies on seasonal timescale
title_fullStr	Evaluation of the INM RAS climate model skill in climate indices and stratospheric anomalies on seasonal timescale
title_full_unstemmed	Evaluation of the INM RAS climate model skill in climate indices and stratospheric anomalies on seasonal timescale
title_sort	evaluation of the inm ras climate model skill in climate indices and stratospheric anomalies on seasonal timescale
publisher	Taylor & Francis Group
publishDate	2021
url	https://doaj.org/article/6734debdec6241468e3308130f61b642
work_keys_str_mv	AT vasilisavorobyeva evaluationoftheinmrasclimatemodelskillinclimateindicesandstratosphericanomaliesonseasonaltimescale AT evgenyvolodin evaluationoftheinmrasclimatemodelskillinclimateindicesandstratosphericanomaliesonseasonaltimescale
_version_	1718404996268032000

Evaluation of the INM RAS climate model skill in climate indices and stratospheric anomalies on seasonal timescale

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