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Data · dataset · 2026

A new method for interpreting nonstationary running correlations and its application to the ENSO-EAWM relationship

Listed in National Center for Atmospheric Research

We here propose a new statistical method to interpret nonstationary running correlations by decomposing them into a stationary part and a first-order Taylor expansion approximation for the nonstationary part.

Description

Then, this method is applied to investigate the nonstationary behavior of the El Nino-Southern Oscillation (ENSO)-East Asian winter monsoon (EAWM) relationship, which exhibits prominent multidecadal variations. It is demonstrated that the first-order approximation of the nonstationary part can be expressed to a large extent by the impact of the nonlinear interaction between the Atlantic Multidecadal Oscillation (AMO) and ENSO (AMO*Nino3.4) on the EAWM.

Therefore, the nonstationarity in the ENSO-EAWM relationship comes predominantly from the impact of an AMO modulation on the ENSO-EAWM teleconnection via this key nonlinear interaction. This general method can be applied to investigate nonstationary relationships that are often observed between various different climate phenomena.

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National Center for Atmospheric Research0e28509c-44eb-4230-af1f-9a66c3e20add13 d agoJSON v1
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concepts[field].local:field:earth-environmentalmapping · data ucar educonnector:data_ucar_edu@1.0.0
concepts[field].local:field:ocean-atmosphericmapping · data ucar educonnector:data_ucar_edu@1.0.0
created_datesource · data ucar educonnector:data_ucar_edu@1.0.0
descriptionsource · data ucar educonnector:data_ucar_edu@1.0.0/notes
publication_datesource · data ucar educonnector:data_ucar_edu@1.0.0
titlesource · data ucar educonnector:data_ucar_edu@1.0.0/title
updated_datesource · data ucar educonnector:data_ucar_edu@1.0.0