Causality and Information Transfer across Time Scales

0508386 - ÚI 2020 RIV SK eng C - Conference Paper (international conference)
Paluš, Milan
Causality and Information Transfer across Time Scales.
Measurement 2019. Proceedings of the 12th International Conference on Measurement. Bratislava, Piscataway: Institute of Measurement Science SAS, IEEE, 2019 - (Maňka, J.; Švehlíková, J.; Witkovský, V.; Frollo, I.), s. 92-101. ISBN 978-80-972629-3-8.
[Measurement 2019. The International Conference on Measurement /12./. Smolenice (SK), 27.05.2019-29.05.2019]
R&D Projects: GA ČR(CZ) GA19-16066S
Institutional support: RVO:67985807
Keywords : Granger Causality * Information Transfer * Interactions * Multiscale Dynamics * causality * coupling * information transfer * synchronization * time scales
OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
http://www.measurement.sk/M2019/

An information-theoretic approach for detecting interactions and information transfer between the two systems is extended to interactions between dynamical phenomena evolving on different time scales of a complex, multiscale process. The approach is applied to about a century-long records of daily mean surface air temperature from various European locations. An information transfer from larger to smaller time scales has been observed as the influence of the phase of slow oscillatory phenomena with the periods around 6-11 years on the amplitudes of the variability characterized by the smaller temporal scales from a few months to 4-5 years. These directed cross-scale interactions have a non-negligible effect on interannual air temperature variability in a large area of Europe.
Permanent Link: http://hdl.handle.net/11104/0299314