| DOI: | 10.1002/2013GL057752
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| 论文题名: | Multicycle ensemble forecasting of sea surface temperature |
| 作者: | Brassington G.B.
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| 刊名: | Geophysical Research Letters
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| ISSN: | 0094-8311
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| EISSN: | 1944-8042
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| 出版年: | 2013
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| 卷: | 40, 期:23 | | 起始页码: | 6191
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| 结束页码: | 6195
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| 语种: | 英语
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| 英文关键词: | ensemble forecasting
; multicycle
; sea surface temperature
; time lagged
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| Scopus关键词: | Background field
; Efficient sampling
; Ensemble averages
; Ensemble forecasting
; Multi-cycle
; Sea surface temperature (SST)
; Sequential systems
; time lagged
; Atmospheric temperature
; Oceanography
; Random errors
; Forecasting
; atmospheric modeling
; ensemble forecasting
; forecasting method
; global ocean
; sea surface temperature
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| 英文摘要: | A novel extension to time-lagged ensemble forecasting called multicycle ensemble forecasting improves the independent sampling of forecast model errors. Multicycle is defined such that each forecast cycle is independent of the previous forecast cycle. For an M cycle system the background field for each cycle is from a model hindcast M cycles earlier. The model errors have a factor M longer period to grow compared with a sequential system; however, the increased independence in the forecast model errors provide weighted ensemble averages with greater skill and reliability over the 0 lag forecast and a good spread-error relationship. This cost-efficient technique is relevant to global ocean forecasting where an ensemble method is computationally prohibitive. Key Points Multicycle is a novel extension to time-lagged ensemble forecasting Efficient sampling of random forecast model errors Weighted ensemble averages have improved skill and reliability ©2013. American Geophysical Union. All Rights Reserved. |
| URL: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84889841319&doi=10.1002%2f2013GL057752&partnerID=40&md5=561f1168cb67e72c1ce8ff30905891e6
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| Citation statistics: |
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| 资源类型: | 期刊论文
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| 标识符: | http://119.78.100.158/handle/2HF3EXSE/5575
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| Appears in Collections: | 气候减缓与适应
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作者单位: | Centre for Australian Weather, Climate Research, Bureau of Meteorology, PO Box 413, Darlinghurst, Sydney, NSW 1300, Australia
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| Recommended Citation: | |
Brassington G.B.. Multicycle ensemble forecasting of sea surface temperature[J]. Geophysical Research Letters,2013-01-01,40(23).
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