Climate Dynamics

, Volume 39, Issue 3–4, pp 1001–1020 | Cite as

An ensemble estimation of the variability of upper-ocean heat content over the tropical Atlantic Ocean with multi-ocean reanalysis products

  • Jieshun Zhu
  • Bohua Huang
  • Magdalena A. Balmaseda
Article

Abstract

Current ocean reanalysis systems contain considerable uncertainty in estimating the subsurface oceanic state, especially in the tropical Atlantic Ocean. Given this level of uncertainty, it is important to develop useful strategies to identify realistic low-frequency signals optimally from these analyses. In this paper, we present an “ensemble” method to estimate the variability of upper-ocean heat content (HC) in the tropical Atlantic based on multiple-ocean reanalysis products. Six state-of-the-art global ocean reanalaysis products, all of which are widely used in the climate research community, are examined in terms of their HC variability from 1979 to 2007. The conventional empirical orthogonal function (EOF) analysis of the HC anomalies from each individual analysis indicates that their leading modes show significant qualitative differences among analyses, especially for the first modes, although some common characteristics are discernable. Then, the simple arithmetic average (or ensemble mean) is applied to produce an ensemble dataset, i.e., the EM analysis. The leading EOF modes of the EM analysis show quantitatively consistent spatial–temporal patterns with those derived from an alternative EOF technique that maximizes signal-to-noise ratio of the six analyses, which suggests that the ensemble mean generates HC fields with the noise reduced to an acceptable level. The quality of the EM analysis is further validated against AVISO altimetry sea level anomaly (SLA) data and PIRATA mooring station data. A regression analysis with the AVISO SLA data proved that the leading modes in the EM analysis are realistic. It also demonstrated that some reanalysis products might contain higher level of intrinsic noise than others. A quantitative correlation analysis indicates that the HC fields are more realistic in the EM analysis than in individual products, especially over the equatorial regions, with signals contributed from all ensemble members. A direct comparison with the HC anomalies derived from in situ temperature measurements showed that the EM analysis generally gets realistic HC variability at the five chosen PIRATA mooring stations. Overall, these results demonstrate that the EM analysis is a promising alternative for studying physical processes and possibly for initializing climate predictions.

Keywords

Tropical Atlantic variability Upper-ocean heat content Multi-ocean reanalysis products Ensemble estimation 

Notes

Acknowledgments

Funding for this study is provided by the NOAA CVP Program (NA07OAR4310310). The authors would like to thank Drs. J. Shukla and J. Kinter for their guidance and support of this project. We are grateful to two anonymous reviewers for their suggestions and comments. We would also like to thank Dr. V. Krishnamurthy and an anonymous reviewer within COLA for their comments on an earlier version of the manuscript. We thank ECMWF, NCEP, GFDL for providing their ocean data assimilation analysis datasets and Dr. B. Giese for providing the SODA ocean data assimilation analyses. The availability of these datasets makes this analysis possible.

References

  1. Allen MR, Smith LA (1997) Optimal filtering in singular spectrum analysis. Phys Lett 234:419–428CrossRefGoogle Scholar
  2. Balmaseda MA, Mogensen K (2010) Evaluation of the ERA-INTERIM forcing fluxes from an ocean perspective. ECMWF ERA report series no. 6. http://www.ecmwf.int/publications/library/do/references/list/782009
  3. Balmaseda MA, Weaver A (2006) Temperature, salinity, and sea level: climate variability from ocean reanalyses. Paper presented at the CLIVAR/GODAE meeting on ocean synthesis evaluation, August 31–September 1, 2006, ECMWF, Reading, UK. Meeting presentation available at: http://www.clivar.org/organization/gsop/synthesis/groups/Items3_4.ppt. Accessed 26 May 2009
  4. Balmaseda M, Vidard A, Anderson D (2008) The ECMWF system 3 ocean analysis system. Mon Wea Rev 136:3018–3034CrossRefGoogle Scholar
  5. Balmaseda M, Mogensen K, Molteni F, Weaver A (2010) The NEMOVAR-COMBINE ocean re-analysis. COMBINE technical report no. 1. http://www.combine-project.eu/Technical-Reports.1668.0.html
  6. Behringer DW (2005) The global ocean data assimilation system (GODAS) at NCEP, 11th symposium on integrated observing and assimilation systems for the atmosphere, oceans, and land surface (IOAS-AOLS), San Antonio, TX. Amer Meteor Soc, vol 3.3Google Scholar
  7. Carton JA, Giese BS (2008) A reanalysis of ocean climate using simple ocean data assimilation (SODA). Mon Wea Rev 146:2999–3017CrossRefGoogle Scholar
  8. Carton JA, Huang B (1994) Warm events in the tropical Atlantic. J Phys Oceanogr 4:888–903CrossRefGoogle Scholar
  9. Carton JA, Santorelli A (2009) Global decadal upper-ocean heat content as viewed in nine analyses. J Clim 21:6015–6035CrossRefGoogle Scholar
  10. Chang P, Ji L, Li H (1997) A decadal climate variation in the tropical Atlantic Ocean from thermodynamic air-sea interactions. Nature 385:516–518CrossRefGoogle Scholar
  11. Chang P, Ji L, Li H, Penland C, Matrasova L (1998) Prediction of tropical Atlantic sea surface temperature. Geophys Res Lett 25:1193–1196Google Scholar
  12. Chang P, Saravanan R, Ji L, Hegerl GC (2000) The effect of local sea surface temperatures on atmospheric circulation over the tropical Atlantic sector. J Clim 13:2195–2216CrossRefGoogle Scholar
  13. Chao Y, Philander SGH (1993) On the structure of the Southern Oscillation. J Clim 6:450–469CrossRefGoogle Scholar
  14. Chiang JCH, Bitz CM (2005) Influence of high latitude ice cover on the marine intertropical convergence zone. Clim Dyn 25:477–496. doi:10.1007/s00382-005-0040-5 CrossRefGoogle Scholar
  15. Corre L, Terray L, Balmaseda M, Ribes A, Weaver A (2010) Can oceanic reanalyses be used to assess recent anthropogenic changes and low-frequency internal variability of upper ocean temperature? Clim Dyn. doi:10.1007/s00382-010-0950-8
  16. Dee D et al (2011) The ERA-interim reanalysis: configuration and performance of the data assimilation system. Accepted by Quart J Roy Meteor SocGoogle Scholar
  17. Dong B-W, Sutton RT (2002) Adjustment of the coupled ocean- atmosphere system to a sudden change in the thermohaline circulation. Geophys Res Lett 29(15):1728. doi:10.1029/2002GL015229 CrossRefGoogle Scholar
  18. Enfield DB, Mayer DA (1997) Atlantic sea surface temperature variability and its relation to El Niño-Southern Oscillation. J Geophys Res 102(C1):929–945. doi:10.1029/96JC03296 CrossRefGoogle Scholar
  19. Florenchie P, Reason CJC, Lutjeharms JRE, Rouault M, Roy C, Masson S (2004) Evolution of interannual warm and cold events in the southeast Atlantic Ocean. J Clim 17:2318–2334CrossRefGoogle Scholar
  20. Folland C, Palmer T, Parker D (1986) Sahel rainfall and worldwide sea surface temperatures. Nature 320:602–606CrossRefGoogle Scholar
  21. Gemmell AL, Smith GC, Haines K, Blower JD (2009) Validation of ocean model syntheses against hydrography using a new web application. J Op Oceangr 2(2):29–41Google Scholar
  22. Ghil M, Malanotte-Rizzoli P (1991) Data assimilation in meteorology and oceanography. Adv Geophys 33:141–266CrossRefGoogle Scholar
  23. Handoh IC, Bigg GR (2000) A self-sustaining climate mode in the tropical Atlantic, 1995–1997: observations and modelling. Quart J Roy Meteor Soc 126:807–821CrossRefGoogle Scholar
  24. Hastenrath S, Heller L (1977) Dynamics of climatic hazards in northeast Brazil. Quart J Roy Meteor Soc 103:77–92CrossRefGoogle Scholar
  25. Hirst AC, Hastenrath S (1983) Atmosphere–ocean mechanisms of climate anomalies in the Angola–Tropical Atlantic sector. J Phys Oceanogr 13:1146–1157CrossRefGoogle Scholar
  26. Hu Z-Z, Huang B (2007) The predictive skill and the most predictable pattern in the tropical Atlantic: the effect of ENSO. Mon Wea Rev 135:1786–1806CrossRefGoogle Scholar
  27. Huang B (2004) Remotely forced variability in the tropical Atlantic Ocean. Climate Dyn 23:133–152CrossRefGoogle Scholar
  28. Huang B, Shukla J (1997) Characteristics of the interannual and decadal variability in a general circulation model of the tropical Atlantic Ocean. J Phys Oceanogr 27:1693–1712CrossRefGoogle Scholar
  29. Huang B, Shukla J (2005) Ocean–atmosphere interactions in the tropical and subtropical Atlantic Ocean. J Clim 18:1652–1672CrossRefGoogle Scholar
  30. Huang B, Carton JA, Shukla J (1995) A numerical simulation of the variability in the tropical Atlantic Ocean, 1980–1988. J Phys Oceanogr 25:835–854CrossRefGoogle Scholar
  31. Huang B, Hu Z-Z, Jha B (2007) Evolution of model systematic errors in the tropical Atlantic basin from the NCEP coupled hindcasts. Clim Dyn 28(7/8):661–682. doi:10.1007/s00382-006-0223-8 CrossRefGoogle Scholar
  32. Joyce TM, Frankignoul C, Yang J, Phillips HE (2004) Ocean response and feedback to the SST dipole in the tropical Atlantic. J Phys Oceanogr 34:2525–2540CrossRefGoogle Scholar
  33. Kanamitsu M, Ebisuzaki W, Woollen J, Yang S-K, Hnilo JJ, Fiorino M, Potter GL (2002) NCEP-DOE AMIP-II reanalysis (R-2). Bull Amer Meteor Soc 83:1631–1643CrossRefGoogle Scholar
  34. Kushnir Y, Robinson WA, Chang P, Robertson AW (2006) The physical basis for predicting Atlantic sector seasonal-to-interannual climate variability. J Clim 23:5949–5970CrossRefGoogle Scholar
  35. Lamb PJ (1978) Large-scale tropical Atlantic surface circulation patterns associated with subsaharan weather anomalies. Tellus 30:240–251CrossRefGoogle Scholar
  36. Le Traon PY, Nadal F, Ducet N (1998) An improved mapping method of multi-satellite altimeter data. J. Atmos Oceanic Technol 25:522–534CrossRefGoogle Scholar
  37. Lee S-K, Wang C (2008) Tropical Atlantic decadal oscillation and its potential impact on the equatorial atmosphere-ocean dynamics: a simple model study. J Phys Oceanogr 38:193–212CrossRefGoogle Scholar
  38. Lee T, Awaji T, Balmaseda MA, Grenier E, Stammer D (2009) Ocean state estimation for climate research. Oceanography 22:160–167CrossRefGoogle Scholar
  39. Lee T et al (2010) Consistency and fidelity of Indonesian-throughflow total volume transport estimated by 14 ocean data assimilation products. Dyn Atmos Oceans 50:201–223CrossRefGoogle Scholar
  40. Mahajan S, Saravanan R, Chang P (2011) The role of the wind-evaporation-sea surface temperature (WES) feedback as a thermodynamic pathway for the equator-ward propagation of high latitude sea-ice induced cold anomalies. J Clim (in press). doi:10.1175/2010JCLI3455.1
  41. Mogensen K, Balmaseda MA, Weaver AT, Martin M, Vidard A (2009) NEMOVAR: a variational data assimilation system for the NEMO ocean model. ECMWF Newslett 120:17–22Google Scholar
  42. Moura AD, Shukla J (1981) On the dynamics of the droughts in northeast Brazil: observations, theory and numerical experiments with a general circulation model. J Atmos Sci 38:2653–2675CrossRefGoogle Scholar
  43. Nobre P, Shukla J (1996) Variations of sea surface temperature, wind stress, and rainfall over the tropical Atlantic and South America. J Clim 9:2464–2479CrossRefGoogle Scholar
  44. Penland C, Matrosova L (1998) Prediction of tropical Atlantic sea surface temperatures using linear inverse modeling. J Clim 11:483–496CrossRefGoogle Scholar
  45. Rebert JP, Donguy JR, Eldin G, Wyrtki E (1985) Relations between sea level, thermocline depth, heat content, and dynamic height in the tropical Pacific Ocean. J Geophys Res 90:11719–11725CrossRefGoogle Scholar
  46. Reynolds RW, Rayner NA, Smith TM, Stokes DC, Wang WQ (2002) An improved in situ and satellite SST analysis for climate, J. Climate 15(13):1609–1625CrossRefGoogle Scholar
  47. Richter I, Xie S-P (2008) On the origin of equatorial Atlantic biases in coupled general circulation models. Clim. Dyn. 31:587–598CrossRefGoogle Scholar
  48. Ruiz-Barradas A, Carton JA, Nigam S (2000) Structure of interannual-to-decadal climate variability in the tropical At- lantic sector. J Clim 13:3285–3297CrossRefGoogle Scholar
  49. Saha S et al (2010) The NCEP climate forecast system reanalysis. Bull Am Met Soc 91:1015–1057CrossRefGoogle Scholar
  50. Servain J (1991) Simple climatic indices for the tropical Atlantic Ocean and some applications. J Geophys Res 96(C8):15137–15146CrossRefGoogle Scholar
  51. Servain J, Picaut J, Merle J (1982) Evidence of remote forcing in the equatorial Atlantic Ocean. J Phys Oceanogr 12:457–463CrossRefGoogle Scholar
  52. Servain J, Busalacchi AJ, McPhaden MJ, Moura AD, Reverdin G, Vianna M, Zebiak SE (1998) A pilot research moored array in the tropical atlantic (PIRATA). Bull Am Meteorol Soc 79:2019–2031CrossRefGoogle Scholar
  53. Servain J, Wainer I, McCreary JP, Dessier A (1999) Relationship between the Equatorial and meridional modes of cli- matic variability in the tropical Atlantic. Geophys Res Lett 26:485–488CrossRefGoogle Scholar
  54. Stammer et al (2010) Ocean information provided through ensemble ocean syntheses. In Hall J, Harrison DE, Stammer D (eds) Proceedings of “OceanObs’09: sustained ocean observations and information for society” conference, vol 2, Venice, Italy, 21–25 September 2009, ESA Publication WPP-306Google Scholar
  55. Stockdale TN, Balmaseda M, Vidard A (2006) Tropical Atlantic SST prediction with coupled ocean–atmosphere GCMs. J Clim 19:6047–6061CrossRefGoogle Scholar
  56. Sutton RT, Jewson SP, Rowell DP (2000) The elements of climate variability in the tropical Atlantic region. J Clim 13:3261–3284CrossRefGoogle Scholar
  57. Venzke S, Allen MR, Sutton RT, Rowell DP (1999) The atmospheric response over the North Atlantic to decadal changes in sea surface temperature. J Clim 12:2562–2584CrossRefGoogle Scholar
  58. Wagner RG, da Silver A (1994) Surface conditions associated with anomalous rainfall in the Guinea coastal region. Int J Climatol 14:179–199CrossRefGoogle Scholar
  59. Wahl S, Latif M, Park W, Keenlyside N (2011) On the tropical atlantic SST warm bias in the Kiel climate model. Clim Dyn 36:891–906CrossRefGoogle Scholar
  60. Wen C, Chang P, Saravanan R (2009) Effect of atlantic meridional overturning circulation changes on tropical atlantic sea-surface temperature variability: A 2-1/2 layer reduced gravity ocean model study. J Clim. doi:10.1175/2009JCLI3042.1
  61. Xie S-P (1999) A dynamic ocean–atmosphere model of the tropical Atlantic decadal variability. J Clim 12:64–70CrossRefGoogle Scholar
  62. Xie S-P, Carton JA (2004) Tropical Atlantic variability: patterns, mechanisms, and impacts. In: Wang C, Xie S-P, Carton JA (eds) Earth’s climate: the ocean–atmosphere interaction. Geophys- ical Monograph, NO. 147, Amer Geophys. Union, Washington DC, pp 121–142CrossRefGoogle Scholar
  63. Xue Y et al (2011a) Comparative analysis of upper ocean heat content variability from ensemble operational ocean analysis. U.S. CLIVAR 9(1):7–10Google Scholar
  64. Xue Y, Huang B, Hu Z, Kumar A, Wen C, Behringer D, Nadiga S (2011b) An assessment of oceanic variability in the NCEP climate forecast system reanalysis. Clim Dyn. doi:10.1007/s00382-010-0954-4
  65. Yang JY (1999) A linkage between decadal climate variations in the Labrador Sea and the tropical Atlantic Ocean. Geophys Res Lett 26:1023–1026CrossRefGoogle Scholar
  66. Zebiak SE (1993) Air–sea interaction in the equatorial Atlantic region. J Clim 8:1567–1586CrossRefGoogle Scholar
  67. Zhang S, Harrison MJ, Rosati A, Wittenberg A (2007) System design and evaluation of coupled ensemble data assimilation for global oceanic climate studies. Mon Wea Rev 135:3541–3564CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • Jieshun Zhu
    • 1
  • Bohua Huang
    • 1
    • 2
  • Magdalena A. Balmaseda
    • 3
  1. 1.Center for Ocean–Land–Atmosphere StudiesInstitute of Global Environment and SocietyCalvertonUSA
  2. 2.Department of Atmospheric, Oceanic, and Earth Sciences, College of ScienceGeorge Mason UniversityFairfaxUSA
  3. 3.European Center for Medium-Range Weather ForecastsReadingUK

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