Ubiquity of human-induced changes in climate variability
Cited 32 time in
Cited 35 time in
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Title
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Ubiquity of human-induced changes in climate variability
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Other Titles
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인간활동 기인 기후변동성 변화의 편재성
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Authors
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Rodgers, Keith B.
Lee, Sun-Seon
Rosenbloom, Nan
Timmermann, Axel
Danabasoglu, Gokhan
Deser, Clara
Edwards, Jim
Kim, Ji-Eun
Simpson, Isla R.
Stein, Karl
Stuecker, Malte F.
Yamaguchi, Ryohei
Bodai, Tamas
Chung, Eui-Seok
Huang, Lei
Kim, Who M.
Lamarque, Jean-Francois
Lombardozzi, Danica L.
Wieder, William R.
Yeager, Stephen G.
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Subject
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Geology
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Keywords
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EL-NINO; TEMPERATURE VARIABILITY; COMBINATION-MODE; FUTURE CHANGES; EARTH SYSTEM; OCEAN; ATMOSPHERE; INCREASE; CARBON; ENSO
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Issue Date
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2021-12-09
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Citation
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Rodgers, Keith B., et al. 2021. "Ubiquity of human-induced changes in climate variability". EARTH SYSTEM DYNAMICS, 12(4): 1393-1411.
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Abstract
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While climate change mitigation targets necessarily concern maximum mean state changes, understanding impacts and developing adaptation strategies will be largely contingent on how climate variability responds to increasing anthropogenic perturbations. Thus far Earth system modeling efforts have primarily focused on projected mean state changes and the sensitivity of specific modes of climate variability, such as the El Nino-Southern Oscillation. However, our knowledge of forced changes in the overall spectrum of climate variability and higher order statistics is relatively limited. Here we present a new 100-member Large Ensemble of climate change projections conducted with the Community Earth System Model version 2 over 1850-2100 to examine the sensitivity of internal climate fluctuations to greenhouse warming. Our unprecedented simulations reveal that changes in variability, considered broadly in terms of probability, distribution, amplitude, frequency, phasing, and patterns, are ubiquitous and span a wide range of physical and ecosystem variables across many spatial and temporal scales. Greenhouse warming in the model in alters variance spectra of Earth system variables that are characterized by non-Gaussian probability distributions, such as rainfall, primary production, or fire occurrence. Our modeling results have important implications for climate adaptation efforts, resource management, seasonal predictions, and for assessing potentialstressors for terrestrial and marine ecosystems.
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URI
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https://repository.kopri.re.kr/handle/201206/13610
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DOI
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http://dx.doi.org/10.5194/esd-12-1393-2021
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Type
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Article
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Station
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해당사항없음
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Indexed
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SCIE
- Appears in Collections
- 2021-2021, Earth System Model-based Korea Polar Prediction System (KPOPS-Earth) Development and Its Application to the High-impact Weather Events originated from the Changing Arctic Ocean and Sea Ice (21-21) / Kim, Joo-Hong (PE21010)
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