Anthropogenic carbon dioxide transport in the Southern Ocean driven by Ekman flow

Nature ◽  
2010 ◽  
Vol 463 (7277) ◽  
pp. 80-83 ◽  
Author(s):  
T. Ito ◽  
M. Woloszyn ◽  
M. Mazloff
2006 ◽  
Vol 19 (24) ◽  
pp. 6382-6390 ◽  
Author(s):  
Joellen L. Russell ◽  
Keith W. Dixon ◽  
Anand Gnanadesikan ◽  
Ronald J. Stouffer ◽  
J. R. Toggweiler

Abstract A coupled climate model with poleward-intensified westerly winds simulates significantly higher storage of heat and anthropogenic carbon dioxide by the Southern Ocean in the future when compared with the storage in a model with initially weaker, equatorward-biased westerlies. This difference results from the larger outcrop area of the dense waters around Antarctica and more vigorous divergence, which remains robust even as rising atmospheric greenhouse gas levels induce warming that reduces the density of surface waters in the Southern Ocean. These results imply that the impact of warming on the stratification of the global ocean may be reduced by the poleward intensification of the westerlies, allowing the ocean to remove additional heat and anthropogenic carbon dioxide from the atmosphere.


2003 ◽  
Vol 17 (2) ◽  
pp. n/a-n/a ◽  
Author(s):  
Noah S. Diffenbaugh ◽  
Lisa C. Sloan ◽  
Mark A. Snyder ◽  
Jason L. Bell ◽  
Jed Kaplan ◽  
...  

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jianbin Tao ◽  
XiangBing Kong

AbstractA gridded social-economic data is essential for geoscience analysis and multidisciplinary application. Spatial allocation of carbon dioxide statistics data is an important issue in the context of global climate change, which involves the carbon emissions accounting and decomposition of responsibility for carbon emission reductions. In this research a new spatial allocation method for non-point source anthropogenic carbon dioxide emissions (ACDE) fusing multi-source data using Bayesian Network (BN) was introduced. In addition to common-used DMSP (Defense Meteorological Satellite Program), PD (population density) and GDP (Gross Domestic Production) data, the land cover and vegetation data was imported into the model as prior knowledge to optimize the model fitting. The prior knowledge here was based on the understanding that ACDE was dominated by human activities and has strong correlations with land cover and vegetation conditions. A 1 km gridded ACDE map integrated emissions form point-source and non-point source was generated and validated. The model predicts ACDE with high accuracies and great improvement can be observed when fusing land cover and vegetation as prior knowledge. The model can achieve successful statistics data downscaling on national scale provided adequate sample data are available, offering a novel method for ACDE accounting in China.


2021 ◽  
Author(s):  
Yannig Durand ◽  
Grégory Bazalgette Courrèges-Lacoste ◽  
Charlotte Pachot ◽  
Luc Boucher ◽  
Arnaud Pasquet ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document