可预测性
环境科学
碳汇
水槽(地理)
初始化
气候学
碳循环
地球大气中的二氧化碳
气候模式
固碳
热带
二氧化碳
温室气体
大气科学
气候变化
地质学
海洋学
地理
生态学
计算机科学
数学
生态系统
统计
生物
地图学
程序设计语言
作者
Tatiana Ilyina,LI Hong-mei,Aaron Spring,Wolfgang A. Müller,Laurent Bopp,M. O. Chikamoto,Gökhan Danabasoglu,Mikhail Dobrynin,John Dunne,Filippa Fransner,Pierre Friedlingstein,Woo‐Sung Lee,Nicole S. Lovenduski,William J. Merryfield,Juliette Mignot,Jong Yeon Park,Roland Séférian,Reinel Sospedra‐Alfonso,Michio Watanabe,Stephen Yeager
摘要
Abstract Inter‐annual to decadal variability in the strength of the land and ocean carbon sinks impede accurate predictions of year‐to‐year atmospheric carbon dioxide (CO 2 ) growth rate. Such information is crucial to verify the effectiveness of fossil fuel emissions reduction measures. Using a multi‐model framework comprising prediction systems initialized by the observed state of the physical climate, we find a predictive skill for the global ocean carbon sink of up to 6 years for some models. Longer regional predictability horizons are found across single models. On land, a predictive skill of up to 2 years is primarily maintained in the tropics and extra‐tropics enabled by the initialization of the physical climate. We further show that anomalies of atmospheric CO 2 growth rate inferred from natural variations of the land and ocean carbon sinks are predictable at lead time of 2 years and the skill is limited by the land carbon sink predictability horizon.
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