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Ubiquity of human-induced changes in climate variability

Cited 14 time in wos
Cited 15 time in scopus
Title
Ubiquity of human-induced changes in climate variability
Other Titles
인간활동 기인 기후변동성 변화의 편재성
Authors
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.
Subject
Geology
Keywords
EL-NINOTEMPERATURE VARIABILITYCOMBINATION-MODEFUTURE CHANGESEARTH SYSTEMOCEANATMOSPHEREINCREASECARBONENSO
Issue Date
2021-12-09
Citation
Rodgers, Keith B., et al. 2021. "Ubiquity of human-induced changes in climate variability". EARTH SYSTEM DYNAMICS, 12(4): 1393-1411.
Abstract
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.
URI
https://repository.kopri.re.kr/handle/201206/13610
DOI
http://dx.doi.org/10.5194/esd-12-1393-2021
Type
Article
Station
해당사항없음
Indexed
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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