Predictable Variations of the Carbon Sinks and Atmospheric CO2 Growth in a Multi-Model Framework

被引：24

作者：

Ilyina, T. ^{[1
]}

Li, H. ^{[1
]}

Spring, A. ^{[1
,2
]}

Mueller, W. A. ^{[1
]}

Bopp, L. ^{[3
]}

Chikamoto, M. O. ^{[4
]}

Danabasoglu, G. ^{[5
]}

Dobrynin, M. ^{[6
]}

Dunne, J. ^{[7
]}

Fransner, F. ^{[8
,9
]}

Friedlingstein, P. ^{[10
]}

Lee, W. ^{[11
]}

Lovenduski, N. S. ^{[12
,13
]}

Merryfield, W. J. ^{[11
]}

Mignot, J. ^{[14
]}

Park, J. Y. ^{[15
]}

Seferian, R. ^{[16
]}

Sospedra-Alfonso, R. ^{[11
]}

Watanabe, M. ^{[17
]}

Yeager, S. ^{[5
]}

机构：

[1] Max Planck Inst Meteorol, Hamburg, Germany

[2] Int Max Planck Res Sch Earth Syst Modelling, Hamburg, Germany

[3] Sorbonne Univ, PSL Res Univ, Ecole Normale Super, CNRS,Ecole Polytech,LMD,IPSL, Paris, France

[4] Univ Texas Austin, Jackson Sch Geosci, Inst Geophys, Austin, TX 78712 USA

[5] Natl Ctr Atmospher Res, POB 3000, Boulder, CO 80307 USA

[6] Deutsch Wetterdienst DWD, Hamburg, Germany

[7] NOAA, OAR Geophys Fluid Dynam Lab, Princeton, NJ USA

[8] Univ Bergen, Geophys Inst, Bergen, Norway

[9] Bjerknes Ctr Climate Res, Bergen, Norway

[10] Univ Exeter, Coll Engn Math & Phys Sci, Exeter, Devon, England

[11] Environm & Climate Change Canada, Canadian Ctr Climate Modelling & Anal, Victoria, BC, Canada

[12] Univ Colorado, Dept Atmospher & Ocean Sci, Boulder, CO 80309 USA

[13] Univ Colorado, Inst Arctic & Alpine Res, Boulder, CO 80309 USA

[14] Sorbonne Univ, CNRS, MNHN, LOCEAN,IRD, Paris, France

[15] Jeonbuk Natl Univ, Dept Earth & Environm Sci, Jeollabuk Do, South Korea

[16] Univ Toulouse, CNRS, Meteo France, CNRM, Toulouse, France

[17] Japan Agcy Marine Earth Sci & Technol JAMSTE, Res Inst Global Change, Yokohama, Kanagawa, Japan

来源：

GEOPHYSICAL RESEARCH LETTERS | 2021年 / 48卷 / 06期

基金：

美国国家科学基金会; 新加坡国家研究基金会;

关键词：

atmospheric CO2; carbon sinks; predictions; EARTH SYSTEM MODEL; GLOBAL OCEAN BIOGEOCHEMISTRY; EL-NINO; DATA ASSIMILATION; SURFACE-TEMPERATURE; VARIABILITY; INITIALIZATION; UNCERTAINTY; PERFORMANCE; SALINITY;

D O I：

10.1029/2020GL090695

中图分类号：

P [天文学、地球科学];

学科分类号：

07 ;

摘要：

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 (CO2) 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 CO2 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.

引用

页数：12

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