Dynamics of climate networks
A methodology to analyze dynamical changes in dynamic climate systems based on complex networks and Information Theory quantifiers is discussed. In particular, the square root of the Jensen-Shannon divergence, a measure of dissimilarity between two probability distributions, is used to quantify stat...
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2012
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| Acceso en línea: | https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_21941009_v20_n_p157_Carpi http://hdl.handle.net/20.500.12110/paper_21941009_v20_n_p157_Carpi |
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paper:paper_21941009_v20_n_p157_Carpi |
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paper:paper_21941009_v20_n_p157_Carpi2023-06-08T16:35:07Z Dynamics of climate networks Climate networks Complex network evolution El Niño/Southern oscillation Information theory quantifiers Jensen-Shannon divergence Shannon entropy Degree distributions Dynamic network topology Information transfers Jensen-Shannon divergence Network evolution Network evolution process Shannon entropy Surface air temperatures Dynamics Electric network topology Information theory Probability distributions Climate change A methodology to analyze dynamical changes in dynamic climate systems based on complex networks and Information Theory quantifiers is discussed. In particular, the square root of the Jensen-Shannon divergence, a measure of dissimilarity between two probability distributions, is used to quantify states in the network evolution process by means of their degree distribution. We explore the evolution of the surface air temperature (SAT) climate network on the Tropical Pacific region. We find that the proposed quantifier is able not only to capture changes in the dynamics of the studied process but also to quantify and compare states in its evolution. The dynamic network topology is investigated for temporal windows of one-year duration over the 1948-2009 period. The use of this novel methodology, allows us to consistently compare the evolving networks topologies and to capture a cyclic behavior consistent with that of El Niño/Southern Oscillation. This cyclic behavior involves alternating states of less/more efficient information transfer during El Niño/La Niña years, respectively, reflecting a higher climatic stability for La Niña years which is in agreement with current observations. The study also detects a change in the dynamics of the network structure, which coincides with the 76/77 climate shift, after which, conditions of less-efficient information transfer are more frequent and intense. © Springer Science+Business Media New York 2012. 2012 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_21941009_v20_n_p157_Carpi http://hdl.handle.net/20.500.12110/paper_21941009_v20_n_p157_Carpi |
| institution |
Universidad de Buenos Aires |
| institution_str |
I-28 |
| repository_str |
R-134 |
| collection |
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) |
| topic |
Climate networks Complex network evolution El Niño/Southern oscillation Information theory quantifiers Jensen-Shannon divergence Shannon entropy Degree distributions Dynamic network topology Information transfers Jensen-Shannon divergence Network evolution Network evolution process Shannon entropy Surface air temperatures Dynamics Electric network topology Information theory Probability distributions Climate change |
| spellingShingle |
Climate networks Complex network evolution El Niño/Southern oscillation Information theory quantifiers Jensen-Shannon divergence Shannon entropy Degree distributions Dynamic network topology Information transfers Jensen-Shannon divergence Network evolution Network evolution process Shannon entropy Surface air temperatures Dynamics Electric network topology Information theory Probability distributions Climate change Dynamics of climate networks |
| topic_facet |
Climate networks Complex network evolution El Niño/Southern oscillation Information theory quantifiers Jensen-Shannon divergence Shannon entropy Degree distributions Dynamic network topology Information transfers Jensen-Shannon divergence Network evolution Network evolution process Shannon entropy Surface air temperatures Dynamics Electric network topology Information theory Probability distributions Climate change |
| description |
A methodology to analyze dynamical changes in dynamic climate systems based on complex networks and Information Theory quantifiers is discussed. In particular, the square root of the Jensen-Shannon divergence, a measure of dissimilarity between two probability distributions, is used to quantify states in the network evolution process by means of their degree distribution. We explore the evolution of the surface air temperature (SAT) climate network on the Tropical Pacific region. We find that the proposed quantifier is able not only to capture changes in the dynamics of the studied process but also to quantify and compare states in its evolution. The dynamic network topology is investigated for temporal windows of one-year duration over the 1948-2009 period. The use of this novel methodology, allows us to consistently compare the evolving networks topologies and to capture a cyclic behavior consistent with that of El Niño/Southern Oscillation. This cyclic behavior involves alternating states of less/more efficient information transfer during El Niño/La Niña years, respectively, reflecting a higher climatic stability for La Niña years which is in agreement with current observations. The study also detects a change in the dynamics of the network structure, which coincides with the 76/77 climate shift, after which, conditions of less-efficient information transfer are more frequent and intense. © Springer Science+Business Media New York 2012. |
| title |
Dynamics of climate networks |
| title_short |
Dynamics of climate networks |
| title_full |
Dynamics of climate networks |
| title_fullStr |
Dynamics of climate networks |
| title_full_unstemmed |
Dynamics of climate networks |
| title_sort |
dynamics of climate networks |
| publishDate |
2012 |
| url |
https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_21941009_v20_n_p157_Carpi http://hdl.handle.net/20.500.12110/paper_21941009_v20_n_p157_Carpi |
| _version_ |
1768544340644200448 |