The Ocean Reanalyses Intercomparison Project (ORA-IP)

作者：Magdalena Alonso Balmaseda, Fabrice Hernández, Andrea Storto, Matthew D. Palmer, Oscar Alves, Li Shi, G. C. Moore Smith, Takahiro Toyoda, Maria Valdivieso, Bernard Barnier, David Behringer, Tim Boyer, You‐Soon Chang, Gennady A. Chepurin, Nicolas Ferry, Gaël Forget, Yosuke Fujii, Simon Good, S. Guinehut, Keith Haines, Yoichi Ishikawa, Sarah P. E. Keeley, Armin Köhl, Tong Lee, Matthew James Martin, Simona Masina, Shuhei Masuda, Benoît Meyssignac, Kristian S. Mogensen, L. Parent, K. Andrew Peterson, Yongming Tang, Yonghong Yin, G. Vernières, Xin Wang, Jennifer C. Waters, Robin Wedd, O. Wang, Yuan Xue, Matthieu Chevallier, J-F. Lemieux, Frederick Dupont, Tsurane Kuragano, Masafumi Kamachi, Toshiyuki Awaji, Nico Caltabiano, Kirsten Wilmer-Becker, F. Gaillard · 发表于：Journal of Operational Oceanography · 年份：2015 · DOI：10.1080/1755876x.2015.1022329 · 被引用次数：316 · 研究领域：Climate variability and models、Oceanographic and Atmospheric Processes、Arctic and Antarctic ice dynamics

Uncertainty in ocean analysis methods and deficiencies in the observing system are major obstacles for the reliable reconstruction of the past ocean climate. The variety of existing ocean reanalyses is exploited in a multi-reanalysis ensemble to improve the ocean state estimation and to gauge uncertainty levels. The ensemble-based analysis of signal-to-noise ratio allows the identification of ocean characteristics for which the estimation is robust (such as tropical mixed-layer-depth, upper ocean heat content), and where large uncertainty exists (deep ocean, Southern Ocean, sea ice thickness, salinity), providing guidance for future enhancement of the observing and data assimilation systems.