Representation of Modes of Atmospheric Circulation Variability by Self-Organizing Maps: A Study Using Synthetic Data

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68378289%3A_____%2F23%3A00576915" target="_blank" >RIV/68378289:_____/23:00576915 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216208:11310/23:10470579

Výsledek na webu

<a href="https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JD039183" target="_blank" >https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JD039183</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1029/2023JD039183" target="_blank" >10.1029/2023JD039183</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Representation of Modes of Atmospheric Circulation Variability by Self-Organizing Maps: A Study Using Synthetic Data

Popis výsledku v původním jazyce

Self-organizing maps (SOMs) represent a popular tool for classifying atmospheric circulation patterns. One of their traditional applications has been to link typical synoptic-scale patterns to large-scale teleconnections, or modes of low-frequency circulation variability. However, recently there have been attempts to interpret an array of SOM nodes directly as a continuum of teleconnections, grounded in SOMs' ability to combine two otherwise distinct approaches to data analysis, that is, exploratory projection (or, dimensionality reduction) and classification. This conceptual shift calls for methodological studies that would improve our understanding of how orthogonal modes of variability, typically used to describe teleconnections, relate to SOM outputs. Here, we define three idealized modes of variability and use their various combinations to generate synthetic data sets. Many variants of SOMs are generated for SOMs of various shapes and sizes. The results show that projection of modes on a SOM array is sensitive not only to data structure, but also to various SOM parameters. The leading mode of variability projects rather strongly on SOMs if its explained variance is markedly higher than that of the second-order mode: the remaining modes project considerably more weakly, and all modes tend to blend when their explained variance is similar, which leads to underrepresentation of some phases of modes and/or combinations of modes among the SOM patterns. Furthermore, we show that some features of SOM topology that were previously considered a proof of data nonlinearity appear even if the underlying modes of variability are strictly linear.

Název v anglickém jazyce

Representation of Modes of Atmospheric Circulation Variability by Self-Organizing Maps: A Study Using Synthetic Data

Popis výsledku anglicky

Self-organizing maps (SOMs) represent a popular tool for classifying atmospheric circulation patterns. One of their traditional applications has been to link typical synoptic-scale patterns to large-scale teleconnections, or modes of low-frequency circulation variability. However, recently there have been attempts to interpret an array of SOM nodes directly as a continuum of teleconnections, grounded in SOMs' ability to combine two otherwise distinct approaches to data analysis, that is, exploratory projection (or, dimensionality reduction) and classification. This conceptual shift calls for methodological studies that would improve our understanding of how orthogonal modes of variability, typically used to describe teleconnections, relate to SOM outputs. Here, we define three idealized modes of variability and use their various combinations to generate synthetic data sets. Many variants of SOMs are generated for SOMs of various shapes and sizes. The results show that projection of modes on a SOM array is sensitive not only to data structure, but also to various SOM parameters. The leading mode of variability projects rather strongly on SOMs if its explained variance is markedly higher than that of the second-order mode: the remaining modes project considerably more weakly, and all modes tend to blend when their explained variance is similar, which leads to underrepresentation of some phases of modes and/or combinations of modes among the SOM patterns. Furthermore, we show that some features of SOM topology that were previously considered a proof of data nonlinearity appear even if the underlying modes of variability are strictly linear.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10509 - Meteorology and atmospheric sciences

Projekt

<a href="/cs/project/GA17-07043S" target="_blank" >GA17-07043S: Dálkové vazby - hlavní stavební kameny atmosférické cirkulace</a><br>

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2023

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Journal of Geophysical Research-Atmospheres

ISSN

2169-897X

e-ISSN

2169-8996

Svazek periodika

128

Číslo periodika v rámci svazku

20

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

19

Strana od-do

e2023JD039183

Kód UT WoS článku

001089332100009

EID výsledku v databázi Scopus

2-s2.0-85174623416