Information transfer across scales of climate variability in understanding of anomalies and extreme events: from El Niño-Southern Oscillation to precipitation variability in East China
Abstract
Complex dynamics of the Earth atmosphere and climate reflects variability in a huge range of spatial and temporal scales. The nonlinear phenomenon of cross-scale causal interactions can be observed due to the recently introduced methodology [1]. An information-theoretic formulation of the generalized, nonlinear Granger causality uncovers causal influence and information transfer from large-scale modes of climate variability to regional temperature and precipitation variability on short time scales [2]. In the dynamics of the El Niño-Southern Oscillation (ENSO), three principal time scales have been identified: the annual cycle (AC), the quasibiennial (QB) mode(s) and the low-frequency (LF) variability. An intricate causal network of information flows among these modes helps to understand the occurrence of extreme El Niño events, characterized by synchronization of the QB modes and AC, and modulation of the QB amplitude by the LF mode [3].
Cross-scale information transfer plays an important role also in ENSO teleconnections: Studying interactions between the ENSO (Niño3.4 index) and precipitation records from East China, causal influence of the ENSO QB mode on the amplitude of the annual cycle in the precipitation as well as the causal influence of the phase of the ENSO LF mode on the amplitude of the precipitation QB variability have been detected. In a consequence, the precipitation variability in the area between the Yellow River and the Yangtze River is influenced more by the phase of the ENSO LF mode than by the total ENSO variability. On the other hand, in the area south of the Yangtze River, the effect of the total ENSO variability is dominant. The mechanisms of the observed causal links are yet to be understood, however, these results have a potential to improve forecasts of precipitation variability in different areas of East China. Support from the Czech Science Foundation (GACR 19-16066S) is gratefully acknowledged. [1] M. Palus, Phys. Rev. Lett. 112, 078702 (2014) [2] N. Jajcay, J. Hlinka, S. Kravtsov, A. A. Tsonis, M. Palus, Geophys. Res. Lett. 43(2), 902-909 (2016) [3] N. Jajcay, S. Kravtsov, G. Sugihara, A. A. Tsonis, and M. Palus, npj Climate and Atmospheric Science 1, 33 (2018). doi:10.1038/s41612-018-0043-7, https://www.nature.com/articles/s41612-018-0043-7- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2019
- Bibcode:
- 2019AGUFMNG11A..06P
- Keywords:
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- 4430 Complex systems;
- NONLINEAR GEOPHYSICS;
- 4485 Self-organization;
- NONLINEAR GEOPHYSICS;
- 4490 Turbulence;
- NONLINEAR GEOPHYSICS;
- 4499 General or miscellaneous;
- NONLINEAR GEOPHYSICS