Decadal potential predictability of upper ocean heat content over the twentieth century
Decadal potential predictability of upper ocean heat content over the twentieth century
复制标题
二十世纪上层海洋热含量的十年潜在可预测性
DOI:
10.1007/s00382-016-3513-9
复制
发表时间:
2016-12
期刊:
影响因子:
4.6
通讯作者:
Lixin Wu
中科院分区:
文献类型:
--
作者:
Shujun Li;Liping Zhang;Lixin Wu
The statistical method, Average Predictability Time (APT) decomposition, is used in the present paper to estimate the decadal predictability of upper ocean heat content over the global ocean, North Pacific and North Atlantic, respectively. The twentieth century simulations from CMIP5 outputs are the main data sources in this study. On global scale, the leading predictable component is characterized by a warming trend over the majority of oceans, which is related to the anthropogenic forced response. The second predictable component has significant loadings in the North Atlantic, especially in the subtropical region, which originates from the Atlantic Multidecadal Oscillation (AMO) predictability. To separate interactions among different ocean basins, we further maximize APT in individual North Pacific and North Atlantic oceans. It is found that the second and the third predictable component in North Pacific are significantly correlated with the well-known North Pacific Gyre Oscillation mode and the Pacific Decadal Oscillation respectively. Upper limit prediction skill of these two components are on the order of 6 years. In contrast, the most predictable component derived from the North Atlantic features an AMO-like spatial structure with its prediction skill up to 18 years, while the basin mode due to global warming only exists as the third component. This indicates the interdecadal variability in the North Atlantic is strong enough to mask the anthropogenic climate signals. Furthermore, predictability in the real world is also investigated and compared with model results by using observation-based data.
登录
查看更多内容
影响因子:
3.1
作者:
T. DelSole;M. Tippett
通讯作者:
T. DelSole;M. Tippett
影响因子:
64.8
作者:
R. Sutton;R. Sutton;Myles R. Allen;Myles R. Allen
通讯作者:
R. Sutton;R. Sutton;Myles R. Allen;Myles R. Allen
影响因子:
5.2
作者:
Rong‐Hua Zhang
通讯作者:
Rong‐Hua Zhang
影响因子:
18.3
作者:
M. Cane
通讯作者:
M. Cane
影响因子:
--
作者:
Daling Li Yi;Liping Zhang;Lixin Wu
通讯作者:
Daling Li Yi;Liping Zhang;Lixin Wu