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Global patterns of extreme temperature teleconnections using climate network analysis

Urheber*innen

Feng,  Yuhao
External Organizations;

Meng,  Jun
External Organizations;

/persons/resource/Jingfang.Fan

Fan,  Jingfang
Potsdam Institute for Climate Impact Research;

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Zitation

Feng, Y., Meng, J., Fan, J. (2025): Global patterns of extreme temperature teleconnections using climate network analysis. - Chaos, 35, 6, 061106.
https://doi.org/10.1063/5.0276151


Zitierlink: https://publications.pik-potsdam.de/pubman/item/item_33448
Zusammenfassung
Extreme weather events, rare yet profoundly impactful, are often accompanied by severe conditions. Increasing global temperatures are poised to exacerbate these events, resulting in greater human casualties, economic losses, and ecological destruction. Complex global climate interactions, known as teleconnections, can lead to widespread repercussions triggered by localized extreme weather. Understanding these teleconnection patterns is crucial for weather forecasting, enhancing safety, and advancing climate science. Here, we employ climate network analysis to uncover teleconnection patterns associated with extreme day-to-day temperature differences, including both extreme warming and cooling events occurring on a daily basis. Our study results demonstrate that the distances of significant teleconnections initially conform to a power-law decay, signifying a decline in connectivity with distance. However, this power-law decay tendency breaks beyond a certain threshold distance, suggesting the existence of long-distance connections. Additionally, we uncover a greater prevalence of long-distance connectivity among extreme cooling events compared to extreme warming events. The global pattern of teleconnections is, in part, likely driven by the mechanism of Rossby waves, which serve as a rapid conduit for inducing correlated fluctuations in both pressure and temperature. These results enhance our understanding of the multiscale nature of climate teleconnections and hold significant implications for improving weather forecasting and assessing climate risks in a warming world.