Variability of global mean annual temperature is significantly influenced by the rhythm of ocean-atmosphere oscillations

Z. W. Kundzewicz, I. Pińskwar, and D. Koutsoyiannis, Variability of global mean annual temperature is significantly influenced by the rhythm of ocean-atmosphere oscillations, Science of the Total Environment, 747, 141256, doi:10.1016/j.scitotenv.2020.141256, 2020.



While global warming has been evolving over several decades, in particular years there have been considerable deviations of global temperature from the underlying trend. These could be explained by climate variability patterns and, in particular, by the major interplays of atmospheric and oceanic processes that generate variations in the global climatic system. Here we show, in a simple and straightforward way, that a rhythm of the major ocean-atmosphere oscillations, such as the ENSO and IPO in the Pacific as well as the AMO in the Atlantic, is indeed meaningfully influencing the global mean annual temperature. We construct time series of residuals of the global temperature from the medium-term (5-year) running averages and show that these largely follow the rhythm of residuals of three basic ocean-atmosphere oscillation modes (ENSO, IPO and AMO) from the 5-year running averages. We find meaningful correlations between analyzed climate variability and deviations of global mean annual temperature residuals that are robust across various datasets and assumptions and explain over 70% of the annual temperature variability in terms of residuals from medium-term averages.

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Our works referenced by this work:

1. D. Koutsoyiannis, Climate change, the Hurst phenomenon, and hydrological statistics, Hydrological Sciences Journal, 48 (1), 3–24, doi:10.1623/hysj., 2003.
2. D. Koutsoyiannis, and A. Montanari, Statistical analysis of hydroclimatic time series: Uncertainty and insights, Water Resources Research, 43 (5), W05429, doi:10.1029/2006WR005592, 2007.

Our works that reference this work:

1. D. Koutsoyiannis, and Z. W. Kundzewicz, Atmospheric temperature and CO₂: Hen-or-egg causality?, Sci, 2 (4), 83, doi:10.3390/sci2040083, 2020.
2. D. Koutsoyiannis, Rethinking climate, climate change, and their relationship with water, Water, 13 (6), 849, doi:10.3390/w13060849, 2021.
3. D. Koutsoyiannis, C. Onof, A. Christofides, and Z. W. Kundzewicz, Revisiting causality using stochastics: 2. Applications, Proceedings of The Royal Society A, 478 (2261), 20210836, doi:10.1098/rspa.2021.0836, 2022.
4. D. Koutsoyiannis, Stochastics of Hydroclimatic Extremes - A Cool Look at Risk, Edition 3, ISBN: 978-618-85370-0-2, 391 pages, doi:10.57713/kallipos-1, Kallipos Open Academic Editions, Athens, 2023.

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