Identification of Global Warming Contribution to the El Niño Phenomenon Using Empirical Orthogonal Function Analysis

Agromet

View Publication Info
 
 
Field Value
 
Title Identification of Global Warming Contribution to the El Niño Phenomenon Using Empirical Orthogonal Function Analysis
 
Creator Julianto, Mochamad Tito
Dhimas, Septian
Sopaheluwakan, Ardhasena
Nurdiati, Sri
Septiawan, Pandu
 
Subject El Niño
empirical orthogonal function
Pacific Ocean
sea surface temperature
 
Description Sea surface temperature (SST) is identified as one of the essential climate/ocean variables. The increased SST levels worldwide is associated with global warming which is due to excessive amounts of greenhouse gases being released into the atmosphere causing the multi-decadal tendency to warmer SST. Moreover, global warming has caused more frequent extreme El Niño Southern Oscillation (ENSO) events, which are the most dominant mode in the coupled ocean-atmosphere system on an interannual time scale. The objective of this research is to calculate the contribution of global warming to the ENSO phenomenon.  SST anomalies (SSTA) variability rosed from several mechanisms with differing timescales. Therefore, the Empirical Orthogonal Function in this study was used to analyze the data of Pacific Ocean sea surface temperature anomaly. By using EOF analysis, the pattern in data such as precipitation and drought pattern can be obtained. The result of this research showed that the most dominant EOF mode reveals the time series pattern of global warming, while the second most dominant EOF mode reveals the El Niño Southern Oscillation (ENSO). The modes from this EOF method have good performance with 95.8% accuracy rate.
 
Publisher PERHIMPI (Indonesian Association of Agricultural Meteorology)
 
Date 2021-02-19
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
 
Format application/pdf
 
Identifier http://journal.ipb.ac.id/index.php/agromet/article/view/32038
10.29244/j.agromet.35.1.11-19
 
Source Agromet; Vol. 35 No. 1 (2021): JUNE 2021; 11-19
2655-660X
0126-3633
10.29244/j.agromet.35.1
 
Language eng
 
Relation http://journal.ipb.ac.id/index.php/agromet/article/view/32038/21152
 
Rights Copyright (c) 2021 Mochamad Tito Julianto, Septian Dhimas, Ardhasena Sopaheluwakan, Sri Nurdiati, Pandu Septiawan
https://creativecommons.org/licenses/by-nc/4.0
 

Contact Us

The PKP Index is an initiative of the Public Knowledge Project.

For PKP Publishing Services please use the PKP|PS contact form.

For support with PKP software we encourage users to consult our wiki for documentation and search our support forums.

For any other correspondence feel free to contact us using the PKP contact form.

Find Us

Twitter

Copyright © 2015-2018 Simon Fraser University Library