Fenying Cai, Shuheng Lin, Dieter Gerten, Song Yang, Xingwen Jiang, Zhen Su, Jürgen Kurths
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引用次数: 0
Abstract
Tropical convection anomaly could serve as a crucial driver of global atmospheric teleconnections and weather extremes around the world. However, quantifying the dominances of convection anomalies with regional discrepancies, relevant for the variations of global atmospheric circulations, remains challenging. By using a network analysis of observation-based rainfall and ERA5 reanalysis datasets, our study reveals that El Niño-like convection is the most primary rainfall pattern driving the global atmospheric circulation variations. High local concurrences of above-normal rainfall events over equatorial central-eastern Pacific amplify their impacts, even though the most intense rainfall anomalies are observed near the Maritime Continent. Furthermore, we find that the impacts of El Niño-like convection will be tripled by the end of this century, as projected consistently by 23 climate models. Such “rich nodes get richer” phenomenon is probably attributable to the dipolar rainfall changes over the equatorial western-central Pacific. This study highlights the dominant role of El Niño-like convection on the global climate variations, especially under the future changing climate.
期刊介绍:
npj Climate and Atmospheric Science is an open-access journal encompassing the relevant physical, chemical, and biological aspects of atmospheric and climate science. The journal places particular emphasis on regional studies that unveil new insights into specific localities, including examinations of local atmospheric composition, such as aerosols.
The range of topics covered by the journal includes climate dynamics, climate variability, weather and climate prediction, climate change, ocean dynamics, weather extremes, air pollution, atmospheric chemistry (including aerosols), the hydrological cycle, and atmosphere–ocean and atmosphere–land interactions. The journal welcomes studies employing a diverse array of methods, including numerical and statistical modeling, the development and application of in situ observational techniques, remote sensing, and the development or evaluation of new reanalyses.