The ECMWF operational ensemble reanalysis–analysis system for ocean and sea ice: a description of the system and assessment
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Published:2019-06-20
Issue:3
Volume:15
Page:779-808
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ISSN:1812-0792
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Container-title:Ocean Science
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language:en
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Short-container-title:Ocean Sci.
Author:
Zuo HaoORCID, Balmaseda Magdalena AlonsoORCID, Tietsche SteffenORCID, Mogensen Kristian, Mayer Michael
Abstract
Abstract. The ECMWF OCEAN5 system is a global ocean and sea-ice ensemble of reanalysis and real-time analysis. This paper gives a full description
of the OCEAN5 system, with the focus on upgrades of system components with
respect to its predecessors, ORAS4 and ORAP5. An important novelty in OCEAN5
is the ensemble generation strategy that includes perturbation of initial
conditions and a generic perturbation scheme for observations and forcing
fields. Other upgrades include revisions to the a priori bias correction
scheme, observation quality control and assimilation method for sea-level
anomalies. The OCEAN5 historical reconstruction of the ocean and sea-ice
state is the ORAS5 reanalysis, which includes five ensemble members and covers
the period from 1979 onwards. Updated versions of observation data sets are
used in ORAS5 production, with special attention devoted to the consistency
of sea surface temperature (SST) and sea-ice observations. Assessment of
ORAS5 through sensitivity experiments suggests that all system components
contribute to an improved fit to observation in reanalyses, with the most
prominent contribution from direct assimilation of ocean in situ
observations. Results of observing system experiments further suggest that
the Argo float is the most influential observation type in our data assimilation
system. Assessment of ORAS5 has also been carried out for several key ocean
state variables and verified against reference climate data sets from the ESA CCI (European Space Agency Climate Change Initiative) project. With respect to ORAS4, ORAS5 has improved ocean climate state and
variability in terms of SST and sea level, mostly due to increased model
resolution and updates in assimilated observation data sets. In spite of the
improvements, ORAS5 still underestimates the temporal variance of sea level and continues exhibiting large SST biases in the Gulf Stream and its extension
regions which are possibly associated with misrepresentation of front
positions. Overall, the SST and sea-ice uncertainties estimated using five
ORAS5 ensemble members have spatial patterns consistent with those of
analysis error. The ensemble spread of sea ice is commensurable with the
sea-ice analysis error. On the contrary, the ensemble spread is
under-dispersive for SST.
Publisher
Copernicus GmbH
Subject
Cell Biology,Developmental Biology,Embryology,Anatomy
Reference65 articles.
1. Ablain, M., Cazenave, A., Larnicol, G., Balmaseda, M. A., Cipollini, P.,
Faugère, Y., Fernandes, M. J., Henry, O., Johannessen, J. A., Knudsen,
P., Andersen, O., Legeais, J., Meyssignac, B., Picot, N., Roca, M., Rudenko,
S., Scharffenberg, M. G., Stammer, D., Timms, G., and Benveniste, J.:
Improved sea level record over the satellite altimetry era (1993–2010)
from the Climate Change Initiative project, Ocean Sci., 11, 67–82,
https://doi.org/10.5194/os-11-67-2015, 2015. a 2. Balmaseda, M., Hernandez, F., Storto, A., Palmer, M., Alves, O., Shi, L.,
Smith, G., Toyoda, T., Valdivieso, M., Barnier, B., Behringer, D., Boyer, T.,
Chang, Y.-S., Chepurin, G., Ferry, N., Forget, G., Fujii, Y., Good, S.,
Guinehut, S., Haines, K., Ishikawa, Y., Keeley, S., Köhl, A., Lee, T.,
Martin, M., Masina, S., Masuda, S., Meyssignac, B., Mogensen, K., Parent, L.,
Peterson, K., Tang, Y., Yin, Y., Vernieres, G., Wang, X., Waters, J., Wedd,
R., Wang, O., Xue, Y., Chevallier, M., Lemieux, J.-F., Dupont, F., Kuragano,
T., Kamachi, M., Awaji, T., Caltabiano, A., Wilmer-Becker, K., and Gaillard,
F.: The Ocean Reanalyses Intercomparison Project (ORA-IP), J.
Oper. Oceanogr., 8, s80–s97, https://doi.org/10.1080/1755876X.2015.1022329, 2015. a 3. Balmaseda, M. A.: Ocean analysis at ECMWF: From real-time ocean initial
conditions to historical ocean reanalysis, ECMWF Newsletter, 105, 24–42,
2005. a 4. Balmaseda, M. A. and Anderson, D.: Impact of initialization strategies and
observations on seasonal forecast skill, Geophys. Res. Lett.,
36, L01701,
https://doi.org/10.1029/2008GL035561, 2009. a 5. Balmaseda, M. A., Vidard, A., and Anderson, D. L. T.: The ECMWF Ocean
Analysis
System: ORA-S3, Mon. Weather Rev., 136, 3018–3034,
https://doi.org/10.1175/2008MWR2433.1,
2008. a
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