Using an ensemble nonlinear forcing singular vector data assimilation approach to address the ENSO forecast uncertainties caused by the “spring predictability barrier” and El Niño diversity-Reference-Cited by-同舟云学术

Using an ensemble nonlinear forcing singular vector data assimilation approach to address the ENSO forecast uncertainties caused by the “spring predictability barrier” and El Niño diversity

Published:2023-06-01 Issue:11-12 Volume:61 Page:4971-4989
ISSN:0930-7575
Container-title:Climate Dynamics
language:en
Short-container-title:Clim Dyn

Author:

Zheng Yingcong,Duan Wansuo,Tao Lingjiang,Ma Junjie

Funder

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Atmospheric Science

Link

https://link.springer.com/content/pdf/10.1007/s00382-023-06834-3.pdf

Reference57 articles.

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2. Ashok K, Behera SK, Rao SA, Weng HY, Yamagata T (2007) El Nino Modoki and its possible teleconnection. J Geophys Res Oceans 112:27. https://doi.org/10.1029/2006jc003798

3. Barkmeijer J, Iversen T, Palmer TN (2003) Forcing singular vectors and other sensitive model structures. Q J R Meteorol Soc 129:2401–2423. https://doi.org/10.1256/qj.02.126

4. Barnston AG, Tippett MK, L’Heureux ML, Li SH, DeWitt DG (2012) Skill of real-time seasonal ENSO model predictions during 2002–11 is our capability increasing? Bull Amer Meteorol Soc 93:631–651. https://doi.org/10.1175/bams-d-11-00111.1

5. Birgin EG, Martinez JM, Raydan M (2000) Nonmonotone spectral projected gradient methods on convex sets Siam. J Optim 10:1196–1211. https://doi.org/10.1137/s1052623497330963

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