Quantifying the Multivariate ENSO Index (MEI) coupling to CO2 concentration and to the length of day variations

TL;DR

This study investigates the relationships between the Multivariate ENSO Index (MEI), atmospheric CO2 concentrations, and length of day variations, revealing significant coupling and synchronization among these climate and Earth system indicators.

Contribution

It introduces a first-order conversion function to quantify the coupling between MEI and CO2 and LOD variations, enhancing understanding of climate system interactions.

Findings

Extreme MEI values correlate with CO2 rate variations.

MEI is negatively correlated with length of day variations.

Results confirm significant coupling in Earth-atmosphere mechanisms.

Abstract

The El Ni\~no Southern Oscillation (ENSO) is the Earth's strongest climate fluctuation on inter-annual time-scales and has global impacts although originating in the tropical Pacific. Many point indices have been developed to describe ENSO but the Multivariate ENSO Index (MEI) is considered the most representative since it links six different meteorological parameters measured over the tropical Pacific. Extreme values of MEI are correlated to the extreme values of atmospheric CO2 concentration rate variations and negatively correlated to equivalent scale extreme values of the length of day (LOD) rate variation. We evaluate a first order conversion function between MEI and the other two indexes using their annual rate of variation. The quantification of the strength of the coupling herein evaluated provides a quantitative measure to test the accuracy of theoretical model predictions. Our results further confirm the idea that the major local and global Earth-atmosphere system mechanisms are significantly coupled and synchronized to each other at multiple scales.