Climate Dynamics

, Volume 49, Issue 3, pp 1009–1029 | Cite as

An assessment of upper ocean salinity content from the Ocean Reanalyses Inter-comparison Project (ORA-IP)

  • L. Shi
  • O. Alves
  • R. Wedd
  • M. A. Balmaseda
  • Y. Chang
  • G. Chepurin
  • N. Ferry
  • Y. Fujii
  • F. Gaillard
  • S. A. Good
  • S. Guinehut
  • K. Haines
  • F. Hernandez
  • T. Lee
  • M. Palmer
  • K.A. Peterson
  • S. Masuda
  • A. Storto
  • T. Toyoda
  • M. Valdivieso
  • G. Vernieres
  • X. Wang
  • Y. Yin
Article

Abstract

Many institutions worldwide have developed ocean reanalyses systems (ORAs) utilizing a variety of ocean models and assimilation techniques. However, the quality of salinity reanalyses arising from the various ORAs has not yet been comprehensively assessed. In this study, we assess the upper ocean salinity content (depth-averaged over 0–700 m) from 14 ORAs and 3 objective ocean analysis systems (OOAs) as part of the Ocean Reanalyses Intercomparison Project. Our results show that the best agreement between estimates of salinity from different ORAs is obtained in the tropical Pacific, likely due to relatively abundant atmospheric and oceanic observations in this region. The largest disagreement in salinity reanalyses is in the Southern Ocean along the Antarctic circumpolar current as a consequence of the sparseness of both atmospheric and oceanic observations in this region. The West Pacific warm pool is the largest region where the signal to noise ratio of reanalysed salinity anomalies is >1. Therefore, the current salinity reanalyses in the tropical Pacific Ocean may be more reliable than those in the Southern Ocean and regions along the western boundary currents. Moreover, we found that the assimilation of salinity in ocean regions with relatively strong ocean fronts is still a common problem as seen in most ORAs. The impact of the Argo data on the salinity reanalyses is visible, especially within the upper 500 m, where the interannual variability is large. The increasing trend in global-averaged salinity anomalies can only be found within the top 0–300 m layer, but with quite large diversity among different ORAs. Beneath the 300 m depth, the global-averaged salinity anomalies from most ORAs switch their trends from a slightly growing trend before 2002 to a decreasing trend after 2002. The rapid switch in the trend is most likely an artefact of the dramatic change in the observing system due to the implementation of Argo.

Keywords

Ocean reanalyses Salinity content Intercomparison 

References

  1. Ballabrera-Poy J, Murtugudde R, Busalacchi AJ (2002) On the potential impact of sea surface salinity observations on ENSO predictions. J Geophys Res 107(C12):8007. doi: 10.1029/2001JC000834 CrossRefGoogle Scholar
  2. Balmaseda MA, Anderson D, Vidard A (2007) Impact of Argo on analyses of the global ocean. Geophys Res Lett 34:L16605. doi: 10.1029/2007GL030452 Google Scholar
  3. Balmaseda MA, Vidard A, Anderson D (2008) The ECMWF ORA-S3 ocean analysis system. Mon Weather Rev 136:3018–3034CrossRefGoogle Scholar
  4. Balmaseda MA, Alves OJ, Arribas A, Awaji T, Behringer DW, Ferry N, Fujii Y, Lee T, Rienecker M, Rosati T, Stammer D (2009) Ocean initialization for seasonal forecasts. Oceanography 22:154–159CrossRefGoogle Scholar
  5. Balmaseda MA, Mogensen K, Weaver A (2013) Evaluation of the ECMWF ocean reanalysis ORAS4. Q J R Meteor Soc 139:1132–1161CrossRefGoogle Scholar
  6. Balmaseda MA et al (2015) The ocean reanalyses intercomparison project (ORA-IP). J operational oceanography 7:81–99Google Scholar
  7. Behringer DW, Xue Y (2004) Evaluation of the global ocean data assimilation system at NCEP: The Pacific Ocean. In: Eighth symposium on integrated observing and assimilation systems for atmosphere, oceans, and land surface, AMS 84th annual meeting, Washington State Convention and Trade Center, Seattle, WashingtonGoogle Scholar
  8. Belkin IM (2004) Propagation of the “great salinity anomaly” of the 1990s around the northern North Atlantic. Geophys Res Lett 31:L08306. doi: 10.1029/2003GL019334 CrossRefGoogle Scholar
  9. Belkin IM, Levitus S, Antonov J, Malmberg SA (1998) “Great salinity anomalies” in the North Atlantic. Prog Oceanogr 41:1–68CrossRefGoogle Scholar
  10. Boyer TP, Levitus S, Antonov I, Locarnini RA, Garcia HE (2005) Linear trends in salinity for the World Ocean, 1955–1998. Geophys Res Lett 32:L01604. doi: 10.1029/2004GL021791 CrossRefGoogle Scholar
  11. Carton JA, Giese BS (2008) A reanalysis of ocean climate using simple ocean data assimilation (SODA). Mon Weather Rev 136:2999–3017CrossRefGoogle Scholar
  12. Chang Y-S, Zhang S, Rosati A, Delworth T, Stern WF (2012) An assessment of oceanic variability for 1960–2010 from the GFDL ensemble coupled data assimilation. Clim Dyn. doi: 10.1007/s00382-012-1412-2 Google Scholar
  13. Cooper NS (1988) The effect of salinity on tropical ocean model. J Phys Oceanogr 18:697–707CrossRefGoogle Scholar
  14. Cronin MF, McPhaden MJ (1998) Upper ocean salinity balance in the western equatorial Pacific. J Geophys Res 103:27567–27588CrossRefGoogle Scholar
  15. Curry R, Dickson B, Yashayaev I (2003) A change in the freshwater balance of the Atlantic Ocean over the past four decades. Nature 426:826–829CrossRefGoogle Scholar
  16. Dickson RR, Meincke J, Malmberg SA, Lee AJ (1988) The “great salinity anomaly” in the northern North Atlantic, 1968–1982. Prog Oceanogr 20:103–151CrossRefGoogle Scholar
  17. Durack PJ, Wijffels SE (2010) Fifty-year trends in global ocean salinities and their relationship to broad-scale warming. J Clim 23:4342–4362CrossRefGoogle Scholar
  18. Durack PJ, Wijffels SE, Matear RJ (2012) Ocean salinities reveal strong global water cycle intensification during 1950 to 2000. Science 336:455–458CrossRefGoogle Scholar
  19. Fedorov AV, Pacanowski RC, Philander SG, Boccaletti G (2004) The effect of salinity on the wind-driven circulation and the thermal structure of the upper ocean. J Phys Oceanogr 34:1949–1966CrossRefGoogle Scholar
  20. Foltz GR, Grodsky SA, Carton JA (2004) Seasonal salt budget of the north western tropical Atlantic Ocean along 38°W. J Geophys Res 109:C03052. doi: 10.1029/2003JC002111 Google Scholar
  21. Fujii Y, Nakaegawa T, Matsumoto S, Yasuda T, Yamanaka G, Kamachi M (2009) Coupled climate simulation by constraining ocean fields in a coupled model with ocean data. J Clim 22:5541–5557CrossRefGoogle Scholar
  22. Fujii Y, Kamachi M, Matsumoto S, Ishizaki S (2012) Barrier layer and relevant variability of the salinity field in the equatorial Pacific estimated in an ocean reanalysis experiment. Pure appl Geophys 169(3):579–594CrossRefGoogle Scholar
  23. Guinehut S, Dhomps A-L, Larnicol G, Le Traon P-Y (2012) High resolution 3D temperature and salinity fields derived from in situ and satellite observations. Ocean Sci 8:845–857CrossRefGoogle Scholar
  24. Hackert E, Ballabrera-Poy J, Busalacchi A, Zhang RH, Murtugudde R (2011) Impact of sea surface salinity assimilation on coupled forecasts in the tropical Pacific. J Geophys Res 116:C05009. doi: 10.1029/2010JC006708 CrossRefGoogle Scholar
  25. Held IM, Soden BJ (2006) Robust responses of the hydrological cycle to global warming. J Clim 19:5686–5699CrossRefGoogle Scholar
  26. Hernandez F, Bertino L, Brassington G, Chassignet E, Cummings J, Davidson F, Drévillon M, Garric G, Kamachi M, Lellouche J-M, Mahdon R, Martin MJ, Ratsimandresy A, Regnier C (2009) Validation and intercomparison studies within GODAE. Oceanography 22(3):128–143CrossRefGoogle Scholar
  27. Huang B, Xue Y, Behringer DW (2008) Impacts of argo salinity in NCEP global ocean data assimilation system: the tropical Indian Ocean. J Geophys Res 113:C08002. doi: 10.1029/2007JC004388 Google Scholar
  28. Ingleby B, Huddleston M (2007) Quality control of ocean temperature and salinity profiles—historical and real-time data. J Mar Syst 65:158–175CrossRefGoogle Scholar
  29. IPCC (Intergovernmental Panel on Climate Change) (2013) Climate change 2013: the physical science basis. In: Working Group I contribution to the IPCC fifth assessment report. Cambridge University Press, Cambridge, United Kingdom (see www.ipcc.ch/report/ar5/wg1)
  30. Janowiak JE, Bauer P, Wang W, Arkin PA, Gottschalck J (2010) An evaluation of precipitation forecasts from operational models and reanalyses including precipitation variations associated with MJO activity. Mon Weather Rev 138:4542–4560CrossRefGoogle Scholar
  31. Johnson ES, Lagerloef GSE, Gunn JT, Bonjean F (2002) Salinity advection in the tropical oceans compared to atmospheric forcing: a trial balance. J Geophys Res 107:8014CrossRefGoogle Scholar
  32. Kim J-E, Alexander MJ (2013) Tropical precipitation variability and convectively coupled equatorial waves on submonthly time scales in reanalyses and TRMM. J. Climate 26:3013–3030CrossRefGoogle Scholar
  33. Lee T, Awaji T, Balmaseda MA, Greiner E, Stammer D (2009) Ocean state estimation for climate research. Oceanography 22(3):160–167CrossRefGoogle Scholar
  34. Levitus S, Antonov JI, Boyer TP, Locarnini RA, Garcia HE, Mishonov AV (2009) Global ocean heat content 1955–2008 in light of recently revealed instrumentation problems. Geophys Res Lett 36:L07608. doi: 10.1029/2008GL037155 Google Scholar
  35. Levitus S, Antonov JI, Boyer TP, Baranova OK, Garcia HE, Locarnini RA, Mishonov AV, Reagan JR, Seidov D, Yarosh ES, Zweng MM (2012) World ocean heat content and thermosteric sea level change (0–2000 m) 1955–2010. Geophys Res Lett 39:L10603. doi: 10.1029/2012GL051106 CrossRefGoogle Scholar
  36. Maes C, Picaut J, Belamari S (2005) Importance of salinity barrier layer for the buildup of El Niño. J Clim 18:104–118CrossRefGoogle Scholar
  37. Maes C, Ando K, Delcroix T, Kessler WS, McPhaden MJ, Roemmich D (2006) Observed correlation of surface salinity, temperature and barrier layer at the eastern edge of the western Pacific warm pool. Geophys Res Lett 33:L06601. doi: 10.1029/2005GL024772 CrossRefGoogle Scholar
  38. Marshall J, Adcroft A, Hill C, Perelman L, Helsey C (1997) A finite-volume, incompressible Navier–Stokes model for studies of the ocean on parallel computers. J Geophys Res 102:5753–5766CrossRefGoogle Scholar
  39. Masuda S et al (2010) Simulated rapid warming of Abyssal North Pacific waters. Science 329:319–322CrossRefGoogle Scholar
  40. Murtugudde R, Busalacchi AJ (1998) Salinity effects in a tropical ocean model. J Geophys Res 103:3282–3300Google Scholar
  41. O’Kane TJ, Matear RJ, Chamberlain MA, Oke PR (2014) ENSO regimes and the late 1970’s climate shift: the role of synoptic weather and South Pacific Ocean spiciness. J Comp Phys 271:19–38CrossRefGoogle Scholar
  42. Palmer M, et al (2015) Ocean heat content variability and change in an ensemble of ocean reanalyses. Clim Dyn, pp 1–22. doi: 10.1007/s00382-015-2801-0
  43. Rahmstorf S (1996) On the freshwater forcing and transport of the Atlantic thermohaline circulation. Clim Dyn 12:799–811CrossRefGoogle Scholar
  44. Santer BD, Wigley TML, Jones PD (1993) Correlation methods in fingerprint detection studies. Clim Dyn 8:265–276CrossRefGoogle Scholar
  45. Sprintall J, Wijffels SE, Molcard R, Jaya I (2009) Direct estimates of the Indonesian throughflow entering the Indian Ocean: 2004–2006. J Geophys Res Ocean 114:C07001. doi: 10.1029/2008JC005257 CrossRefGoogle Scholar
  46. Storto A, et al (2015) Steric sea level variability (1993–2010) in an ensemble of ocean reanalyses and objective analyses. Clim Dyn, pp 1–21. doi: 10.1007/s00382-015-2554-9
  47. Storto A, Dobricic S, Masina S, Di Pietro P (2011) Assimilating along-track altimetric observations through local hydrostatic adjustments in a global ocean reanalysis system. Mon Weather Rev 139:738–754CrossRefGoogle Scholar
  48. Toyoda T, Fujii Y, Yasuda T, Usui N, Iwao T, Kuragano T, Kamachi M (2013) Improved analysis of the seasonal-interannual fields by a global ocean data assimilation system. Theor Appl Mech Japan 61:31–48Google Scholar
  49. Vernieres G, Rienecker MM, Kovach R, Keppenne LC (2012) The GEOS-iODAS: description and evaluation. In: Tech Rep TM-2012-104606, NASA, National Aeronautics and Space Administration Goddard Space Flight Center, Greenbelt, MDGoogle Scholar
  50. Vialard J, Delecluse P, Menkes C (2002) A modelling study of salinity variability and its effects in the tropical Pacific Ocean during the 1993–1999 period. J Geophys Res 107(C12):8005. doi: 10.1029/2000JC000758 CrossRefGoogle Scholar
  51. Vinje T (2001) Fram Strait ice fluxes and atmospheric circulation, 1950–2000. J Clim 14:3508–3517CrossRefGoogle Scholar
  52. von Storch H, Navarra A (1999) Analysis of climate variability: applications of statistical techniques. Springer, BerlinCrossRefGoogle Scholar
  53. Vranes K, Gordon AL, Ffield A (2002) The heat transport of the Indonesian throughflow and implications for Indian Ocean heat budget. Deep Sea Res I II 49:1391–1410CrossRefGoogle Scholar
  54. Wadley MR, Bigg GR (2006) Are “great salinity anomalies” advective? J Clim 19:1080–1088CrossRefGoogle Scholar
  55. Wang X, Chao Y (2004) Simulated sea surface salinity variability in the tropical Pacific. Geophys Res Lett 31:L02302. doi: 10.1029/2003GL01 CrossRefGoogle Scholar
  56. Waters J, Martin M, While J, Lea D, Weaver A, Mirouze I (2014) Implementing a variational data assimilation system in an operational 1/4 degree global ocean model. Q J R Meteorol Soc. doi: 10.1002/qj.2388 Google Scholar
  57. Xue Y et al (2011) An assessment of oceanic variability in the NCEP climate forecast reanalysis. Clim Dyn 37:2511–2539CrossRefGoogle Scholar
  58. Xue Y et al (2012) A comparative analysis of upper-ocean heat content variability from an ensemble of operational ocean reanalyses. J Clim 25:6905–6929CrossRefGoogle Scholar
  59. Yang SC, Rienecker M, Keppenne C (2010) The impact of ocean data assimilation on seasonal-to-interannual forecasts: a case study of the 2006 El Niño event. J Clim 23:4080–4095CrossRefGoogle Scholar
  60. Yin Y, Alves O, Oke PR (2011) An ensemble ocean data assimilation system for seasonal prediction. Mon Weather Rev 139:786–808CrossRefGoogle Scholar
  61. Zhang R, Vallis GK (2006) Impact of great salinity anomalies on the low-frequency variability of the north Atlantic climate. J Clim 19:470–482CrossRefGoogle Scholar
  62. Zhang S, Harrison MJ, Rosati A, Wittenberg A (2007) System design and evaluation of coupled ensemble data assimilation for global oceanic studies. Mon Weather Rev 135:3541–3564CrossRefGoogle Scholar
  63. Zhao M, Hendon HH, Alves O, Yin Y, Anderson D (2013) Impact of salinity constraints on the simulated mean state and variability in a coupled seasonal forecast model. Mon Weather Rev 141:388–402CrossRefGoogle Scholar
  64. Zhao M, Hendon HH, Alves O, Yin Y (2014) Impact of improved assimilation of temperature and salinity for coupled model seasonal forecasts. Clim Dyn 42:2565–2585CrossRefGoogle Scholar
  65. Zhu J, Huang B, Balmaseda M (2012) An ensemble estimation of the variability of upper-ocean heat content over the tropical Atlantic Ocean with multi-ocean reanalysis products. Clim Dyn 39:1001–1020CrossRefGoogle Scholar
  66. Zhu J, Huang B, Zhang R-H, Hu Z-Z, Kumar A, Balmaseda MA, Marx L, Kinter JL III (2014) Salinity anomaly as a trigger for ENSO events. Nat Sci Rep 4:6821. doi: 10.1038/srep06821 CrossRefGoogle Scholar
  67. Zuo H, Balmaseda MA, Mogensen K (2015) The new eddy-permitting ORAP5 ocean reanalysis: description, evaluation and uncertainties in climate signals. Clim Dyn. doi: 10.1007/s00382-015-2675-1 Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • L. Shi
    • 1
  • O. Alves
    • 1
  • R. Wedd
    • 1
  • M. A. Balmaseda
    • 2
  • Y. Chang
    • 3
    • 16
  • G. Chepurin
    • 4
  • N. Ferry
    • 10
  • Y. Fujii
    • 5
  • F. Gaillard
    • 6
  • S. A. Good
    • 7
  • S. Guinehut
    • 8
  • K. Haines
    • 9
  • F. Hernandez
    • 10
    • 17
  • T. Lee
    • 11
  • M. Palmer
    • 7
  • K.A. Peterson
    • 7
  • S. Masuda
    • 12
  • A. Storto
    • 13
  • T. Toyoda
    • 5
  • M. Valdivieso
    • 9
  • G. Vernieres
    • 14
  • X. Wang
    • 15
  • Y. Yin
    • 1
  1. 1.Research and Development BranchBureau of MeteorologyMelbourneAustralia
  2. 2.European Centre for Medium-Range Weather Forecasting (ECMWF)ReadingUK
  3. 3.Geophysical Fluid Dynamics Laboratory (GFDL)Princeton UniversityPrincetonUSA
  4. 4.University of MarylandCollege ParkUSA
  5. 5.Meteorological Research Institute (MRI)Japan Meteorological AgencyTsukubaJapan
  6. 6.Ifremer, UMR 6523, LPOCNRS/Ifremer/IRD/UBOPlouzaneFrance
  7. 7.Met Office Hadley CentreExeterUK
  8. 8.Collecte Localisation Satellites (CLS)Ramonville Saint‑AgneFrance
  9. 9.NCEOReading UniversityReadingUK
  10. 10.Mercator OcéanRamonville Saint AgneFrance
  11. 11.Jet Propulsion Laboratory (JPL)California Institute of TechnologyPasadenaUSA
  12. 12.Research and Development Center for Global ChangeJapan Agency for Marine-Earth Science and TechnologyYokosukaJapan
  13. 13.Euro-Mediterranean Centre for Climate Change (CMCC)BolognaItaly
  14. 14.Global Modeling and Assimilation Office (GMAO)NASAWashingtonUSA
  15. 15.Joint Institute for Regional Earth System Science and Engineering (JIFRESSE)UCLALos AngelesUSA
  16. 16.Department of Earth ScienceKongju National UniversityGongjuKorea
  17. 17.Institut de Recherche pour le Développement (IRD)ToulouseFrance

Personalised recommendations