Climate Variability Indices—A Guided Tour

The objective of this study is to provide a comprehensive review and characterization of selected climate variability indices. While we discuss many major climate variability mechanisms, we focus on four principal modes of climate variability related to the dynamics of Earth’s oceans and their inter...

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Published in:Geosciences
Main Authors: Mateusz Norel, Michał Kałczyński, Iwona Pińskwar, Krzysztof Krawiec, Zbigniew W. Kundzewicz
Format: Text
Language:English
Published: Multidisciplinary Digital Publishing Institute 2021
Subjects:
Online Access:https://doi.org/10.3390/geosciences11030128
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spelling ftmdpi:oai:mdpi.com:/2076-3263/11/3/128/ 2023-08-20T04:08:15+02:00 Climate Variability Indices—A Guided Tour Mateusz Norel Michał Kałczyński Iwona Pińskwar Krzysztof Krawiec Zbigniew W. Kundzewicz agris 2021-03-10 application/pdf https://doi.org/10.3390/geosciences11030128 EN eng Multidisciplinary Digital Publishing Institute https://dx.doi.org/10.3390/geosciences11030128 https://creativecommons.org/licenses/by/4.0/ Geosciences; Volume 11; Issue 3; Pages: 128 climate variability El Niño-Southern Oscillation North Atlantic Oscillation Pacific Decadal Oscillation Atlantic multi-decadal Oscillation Text 2021 ftmdpi https://doi.org/10.3390/geosciences11030128 2023-08-01T01:14:53Z The objective of this study is to provide a comprehensive review and characterization of selected climate variability indices. While we discuss many major climate variability mechanisms, we focus on four principal modes of climate variability related to the dynamics of Earth’s oceans and their interactions with the atmosphere: the El Niño–Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), Pacific Decadal Oscillation (PDO), and Atlantic Multi-decadal Oscillation (AMO). All these oscillation modes are of broad interest and considerable relevance, also in climate impact studies related to teleconnections, i.e., relationships between climate variations at distant locations. We try to decipher temporal patterns present in time series of different oscillation modes in the ocean–atmosphere system using exploratory analysis of the raw data, their structure, and properties, as well as illustrating the quasi-periodic behavior via wavelet analysis. With this contribution, we hope to help researchers in identifying and selecting data sources and climate variability indices that match their needs. Text North Atlantic North Atlantic oscillation MDPI Open Access Publishing Pacific Geosciences 11 3 128
institution Open Polar
collection MDPI Open Access Publishing
op_collection_id ftmdpi
language English
topic climate variability
El Niño-Southern Oscillation
North Atlantic Oscillation
Pacific Decadal Oscillation
Atlantic multi-decadal Oscillation
spellingShingle climate variability
El Niño-Southern Oscillation
North Atlantic Oscillation
Pacific Decadal Oscillation
Atlantic multi-decadal Oscillation
Mateusz Norel
Michał Kałczyński
Iwona Pińskwar
Krzysztof Krawiec
Zbigniew W. Kundzewicz
Climate Variability Indices—A Guided Tour
topic_facet climate variability
El Niño-Southern Oscillation
North Atlantic Oscillation
Pacific Decadal Oscillation
Atlantic multi-decadal Oscillation
description The objective of this study is to provide a comprehensive review and characterization of selected climate variability indices. While we discuss many major climate variability mechanisms, we focus on four principal modes of climate variability related to the dynamics of Earth’s oceans and their interactions with the atmosphere: the El Niño–Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), Pacific Decadal Oscillation (PDO), and Atlantic Multi-decadal Oscillation (AMO). All these oscillation modes are of broad interest and considerable relevance, also in climate impact studies related to teleconnections, i.e., relationships between climate variations at distant locations. We try to decipher temporal patterns present in time series of different oscillation modes in the ocean–atmosphere system using exploratory analysis of the raw data, their structure, and properties, as well as illustrating the quasi-periodic behavior via wavelet analysis. With this contribution, we hope to help researchers in identifying and selecting data sources and climate variability indices that match their needs.
format Text
author Mateusz Norel
Michał Kałczyński
Iwona Pińskwar
Krzysztof Krawiec
Zbigniew W. Kundzewicz
author_facet Mateusz Norel
Michał Kałczyński
Iwona Pińskwar
Krzysztof Krawiec
Zbigniew W. Kundzewicz
author_sort Mateusz Norel
title Climate Variability Indices—A Guided Tour
title_short Climate Variability Indices—A Guided Tour
title_full Climate Variability Indices—A Guided Tour
title_fullStr Climate Variability Indices—A Guided Tour
title_full_unstemmed Climate Variability Indices—A Guided Tour
title_sort climate variability indices—a guided tour
publisher Multidisciplinary Digital Publishing Institute
publishDate 2021
url https://doi.org/10.3390/geosciences11030128
op_coverage agris
geographic Pacific
geographic_facet Pacific
genre North Atlantic
North Atlantic oscillation
genre_facet North Atlantic
North Atlantic oscillation
op_source Geosciences; Volume 11; Issue 3; Pages: 128
op_relation https://dx.doi.org/10.3390/geosciences11030128
op_rights https://creativecommons.org/licenses/by/4.0/
op_doi https://doi.org/10.3390/geosciences11030128
container_title Geosciences
container_volume 11
container_issue 3
container_start_page 128
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