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Estimating Subseasonal Variability and Trends in Global Atmosphere Using Reanalysis Data

A new measure of subseasonal variability is introduced that provides a scale‐dependent estimation of vertically and meridionally integrated atmospheric variability in terms of the normal modes of linearized primitive equations. Applied to the ERA‐Interim data, the new measure shows that subseasonal...

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Detalles Bibliográficos
Autores principales: Žagar, N., Jelić, D., Alexander, M. J., Manzini, E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6360454/
https://www.ncbi.nlm.nih.gov/pubmed/30774167
http://dx.doi.org/10.1029/2018GL080051
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author Žagar, N.
Jelić, D.
Alexander, M. J.
Manzini, E.
author_facet Žagar, N.
Jelić, D.
Alexander, M. J.
Manzini, E.
author_sort Žagar, N.
collection PubMed
description A new measure of subseasonal variability is introduced that provides a scale‐dependent estimation of vertically and meridionally integrated atmospheric variability in terms of the normal modes of linearized primitive equations. Applied to the ERA‐Interim data, the new measure shows that subseasonal variability decreases for larger zonal wave numbers. Most of variability is due to balanced (Rossby mode) dynamics but the portion associated with the inertio‐gravity (IG) modes increases as the scale reduces. Time series of globally integrated variability anomalies in ERA‐Interim show an increase in variability after year 2000. In recent years the anomalies have been about 2% above the 1981–2010 average. The relative increase in variability projecting on the IG modes is larger and more persistent than for the Rossby modes. Although the IG part is a small component of the subseasonal variability, it is an important effect likely reflecting the observed increase in the tropical precipitation variability.
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spelling pubmed-63604542019-02-14 Estimating Subseasonal Variability and Trends in Global Atmosphere Using Reanalysis Data Žagar, N. Jelić, D. Alexander, M. J. Manzini, E. Geophys Res Lett Research Letters A new measure of subseasonal variability is introduced that provides a scale‐dependent estimation of vertically and meridionally integrated atmospheric variability in terms of the normal modes of linearized primitive equations. Applied to the ERA‐Interim data, the new measure shows that subseasonal variability decreases for larger zonal wave numbers. Most of variability is due to balanced (Rossby mode) dynamics but the portion associated with the inertio‐gravity (IG) modes increases as the scale reduces. Time series of globally integrated variability anomalies in ERA‐Interim show an increase in variability after year 2000. In recent years the anomalies have been about 2% above the 1981–2010 average. The relative increase in variability projecting on the IG modes is larger and more persistent than for the Rossby modes. Although the IG part is a small component of the subseasonal variability, it is an important effect likely reflecting the observed increase in the tropical precipitation variability. John Wiley and Sons Inc. 2018-12-02 2018-12-16 /pmc/articles/PMC6360454/ /pubmed/30774167 http://dx.doi.org/10.1029/2018GL080051 Text en ©2018. The Authors. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Research Letters
Žagar, N.
Jelić, D.
Alexander, M. J.
Manzini, E.
Estimating Subseasonal Variability and Trends in Global Atmosphere Using Reanalysis Data
title Estimating Subseasonal Variability and Trends in Global Atmosphere Using Reanalysis Data
title_full Estimating Subseasonal Variability and Trends in Global Atmosphere Using Reanalysis Data
title_fullStr Estimating Subseasonal Variability and Trends in Global Atmosphere Using Reanalysis Data
title_full_unstemmed Estimating Subseasonal Variability and Trends in Global Atmosphere Using Reanalysis Data
title_short Estimating Subseasonal Variability and Trends in Global Atmosphere Using Reanalysis Data
title_sort estimating subseasonal variability and trends in global atmosphere using reanalysis data
topic Research Letters
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6360454/
https://www.ncbi.nlm.nih.gov/pubmed/30774167
http://dx.doi.org/10.1029/2018GL080051
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