GSTDTAP  > 气候变化
DOI10.1007/s00382-018-4323-z
Remote and local influences in forecasting Pacific SST: a linear inverse model and a multimodel ensemble study
Dias, Daniela Faggiani1; Subramanian, Aneesh1; Zanna, Laure2; Miller, Arthur J.1
2019-03-01
发表期刊CLIMATE DYNAMICS
ISSN0930-7575
EISSN1432-0894
出版年2019
卷号52页码:3183-3201
文章类型Article
语种英语
国家USA; England
英文摘要

A suite of statistical linear inverse models (LIMs) are used to understand the remote and local SST variability that influences SST predictions over the North Pacific region. Observed monthly SST anomalies in the Pacific are used to construct different regional LIMs for seasonal to decadal predictions. The seasonal forecast skills of the LIMs are compared to that from three operational forecast systems in the North American Multi-Model Ensemble (NMME), revealing that the LIM has better skill in the Northeastern Pacific than NMME models. The LIM is also found to have comparable forecast skill for SST in the Tropical Pacific with NMME models. This skill, however, is highly dependent on the initialization month, with forecasts initialized during the summer having better skill than those initialized during the winter. The data are also bandpass filtered into seasonal, interannual and decadal time scales to identify the relationships between time scales using the structure of the propagator matrix. Moreover, we investigate the influence of the tropics and extra-tropics in the predictability of the SST over the region. The Extratropical North Pacific seems to be a source of predictability for the tropics on seasonal to interannual time scales, while the tropics enhance the forecast skill for the decadal component. These results indicate the importance of temporal scale interactions in improving the predictions on decadal timescales. Hence, we show that LIMs are not only useful as benchmarks for estimates of statistical skill, but also to isolate contributions to the forecast skills from different timescales, spatial scales or even model components.


英文关键词Linear inverse model Predictability Sea surface temperature Timescale interactions NMME
领域气候变化
收录类别SCI-E
WOS记录号WOS:000463842700038
WOS关键词SEA-SURFACE TEMPERATURE ; KUROSHIO EXTENSION ; MERIDIONAL MODES ; EASTERN-PACIFIC ; ENSO ; VARIABILITY ; PREDICTABILITY ; SKILL ; PREDICTION ; IMPACT
WOS类目Meteorology & Atmospheric Sciences
WOS研究方向Meteorology & Atmospheric Sciences
引用统计
文献类型期刊论文
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/181447
专题气候变化
作者单位1.Scripps Inst Oceanog, 9500 Gilman Dr 0206, La Jolla, CA 92093 USA;
2.Univ Oxford, Oxford, England
推荐引用方式
GB/T 7714
Dias, Daniela Faggiani,Subramanian, Aneesh,Zanna, Laure,et al. Remote and local influences in forecasting Pacific SST: a linear inverse model and a multimodel ensemble study[J]. CLIMATE DYNAMICS,2019,52:3183-3201.
APA Dias, Daniela Faggiani,Subramanian, Aneesh,Zanna, Laure,&Miller, Arthur J..(2019).Remote and local influences in forecasting Pacific SST: a linear inverse model and a multimodel ensemble study.CLIMATE DYNAMICS,52,3183-3201.
MLA Dias, Daniela Faggiani,et al."Remote and local influences in forecasting Pacific SST: a linear inverse model and a multimodel ensemble study".CLIMATE DYNAMICS 52(2019):3183-3201.
条目包含的文件
条目无相关文件。
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Dias, Daniela Faggiani]的文章
[Subramanian, Aneesh]的文章
[Zanna, Laure]的文章
百度学术
百度学术中相似的文章
[Dias, Daniela Faggiani]的文章
[Subramanian, Aneesh]的文章
[Zanna, Laure]的文章
必应学术
必应学术中相似的文章
[Dias, Daniela Faggiani]的文章
[Subramanian, Aneesh]的文章
[Zanna, Laure]的文章
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。