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Quantifying the effects of observational constraints and uncertainty in atmospheric forcing on historical ocean reanalyses

  • Chunxue Yang
  • Andrea Storto
  • Simona Masina
Article

Abstract

Historical ocean reanalyses combine ocean general circulation models with data assimilation schemes that ingest rescued observations. They can be used as a tool to investigate long-term changes in the ocean climate. However, large uncertainties, due to the poorly developed atmospheric and oceanic observing networks in early periods, still remain. Thus, detailed studies to assess the uncertainty and its time dependency are required to quantify the feasibility of historical ocean reanalyses for climate change assessment. In this work, we estimate the ocean heat content variability from a set of ocean reanalyses that cover the period 1900–2010. The ocean reanalyses include realizations forced by two different atmospheric reanalyses (20CRv2 and ERA-20C), combined with different data assimilation strategies, in the attempt to evaluate the relative weight of the atmospheric forcing and observation uncertainties on the resulting ocean heat content estimates. Results suggest that even when observing networks are poor, the observations are able to shape the upper ocean heat content variability, in terms of long-term trends and reproduction of individual warming/cooling events related to volcanic eruptions. The assimilation of in-situ profiles has an effect even on the sea surface temperature variability and is able to constrain the top 700 m heat content since the 1950s with respect to the uncertainty borne by the atmospheric forcing. The vertical propagation of the upper ocean observational information is however slow (with typically decadal time scale). Consequently, the total column heat content is constrained by observations only in the latest two decades. We conclude that upper ocean heat content diagnostics from historical ocean reanalyses bear the climate change signature and may be considered for long-term studies when complemented by proper uncertainty estimation.

Notes

Acknowledgements

This work was supported by the Ministero dell’Istruzione, dell’Università e della Ricerca (GEMINA).

References

  1. Abraham JP, Baringer M, Bindoff NL, Boyer T, Cheng LJ, Church JA, Conroy JL, Domingues CM, Fasullo JT, Gilson J, Goni G, Good SA, Gorman JM, Gouretski V, Isshii M, Jonhson GC, Kizu S, Lyman JM, Macdonald AM, Minkowycz WJ, Moffitt SE, Palmer MD, Piola AR, Reseghetti F, Schukmann K, Trenberth KE, Velicogna I, Willis JK (2013) A review of global ocean temperature observations: Implication for ocean heat content estimates and climate change. Rev Geophys 51:450–483.  https://doi.org/10.1002/rog.20022 CrossRefGoogle Scholar
  2. Atkinson CP, Rayner NA, Kennedy JJ, Good SA (2014) An integrated database of ocean temperature and salinity observations. J Geophys Res Oceans 119:7139–7163.  https://doi.org/10.1002/2014JC010053 CrossRefGoogle Scholar
  3. Behrens E, Biastoch A, Böning CW (2013) Spurious AMOC trends in global ocean sea-ice models related to subarctic freshwater forcing. Ocean Model 69:39–49CrossRefGoogle Scholar
  4. Bernie DJ, Guilyardi E, Madec G, Slingo JM, Woolnough SJ (2007) Impact of resolving the diurnal cycle in an ocean–atmosphere GCM. Part 1: A diurnally forced OGCM. Clim Dynam 29:575–590CrossRefGoogle Scholar
  5. Bourdalle-Badie R, Treguier AM (2006) A climatology of runoff for the global ocean-ice model ORCA025. MERCATOR report MOO-RP-425-366-MERGoogle Scholar
  6. Boyer TP, Levitus S (1998) Objective analyses of temperature and salinity for the world ocean on a 1/4 grid. NOAA Atlas NESDIS, Washington, DCGoogle Scholar
  7. Boyer TP, Antonov JI, Baranova OK, Garcia HE, Johnson DR, Locarnini RA, Mishonov AV, Seidov D, Smolyar IV, Zweng MM (2009) World Ocean Database 2009, Chap. 1: introduction, NOAA Atlas NESDIS 66, Levitus S (ed), U.S. Gov. Printing Office, Wash., DVD, p 216. https://www.nodc.noaa.gov
  8. Boyer T, Domingues CM, Good SA, Johnson GC, Lyman JM, Ishii M, Gouretski V, Willis JK, Antonov J, Wijffels S, Church JA, Cowley R, Bindoff NL (2016) Sensitivity of global upper-ocean heat content estimates to mapping methods, XBT bias corrections and baseline climatologies. J. Clim 29:4817–4842CrossRefGoogle Scholar
  9. Brönnimann S, Grant AN, Compo GP et al (2012) A multi-data set comparison of the vertical structure of temperature variability and change over the Arctic during the past 100 years. Clim Dyn 39:1577–1598.  https://doi.org/10.1007/s00382-012-1291-6 CrossRefGoogle Scholar
  10. Carton JA, Seidel HF, Giese BS (2012) Detecting historical ocean climate variability. J Geophys Res 117:C02023.  https://doi.org/10.1029/2011JC007401 CrossRefGoogle Scholar
  11. Chen Z, Wu L (2012) Long-term change of the Pacific North Equatorial Current bifurcation in SODA. J Geophys Res 117:C06016.  https://doi.org/10.1029/2011JC007814 Google Scholar
  12. Compo GP, Whitaker JS, Sardeshmukh PD (2006) Feasibility of a 100-year reanalysis using only surface pressure data. Bull Am Meteorol Soc 87:175–190.  https://doi.org/10.1175/BAMS-87-2-175 CrossRefGoogle Scholar
  13. Compo GP, Whitaker JS, Sardeshmukh PD, Matsui N, Allan RJ, Yin X, Gleason BE, Vose RS, Rutledge G, Bessemoulin P, Brönnimann S, Brunet M, Crouthamel RI, Grant AN, Groisman PY, Jones PD, Kruk MC, Kruger AC, Marshall GJ, Maugeri M, Mok HY, Nordli Ø, Ross TF, Trigo RM, Wang XL, Woodruff SD, Worley SJ (2011) The Twentieth Century Reanalysis Project. QJR Meteorol Soc 137:1–28.  https://doi.org/10.1002/qj.776 CrossRefGoogle Scholar
  14. Cram TA, Compo GP, Yin X, Allan RJ, McColl C, Vose RS, Whitaker JS, Matsui N, Ashcroft L, Auchmann R, Bessemoulin P, Brandsma T, Brohan P, Brunet M, Comeaux J, Crouthamel R, Gleason BE, Groisman PY, Hersbach H, Jones PD, Jónsson T, Jourdain S, Kelly G, Knapp KR, Kruger A, Kubota H, Lentini G, Lorrey A, Lott N, Lubker SJ, Luterbacher J, Marshall GJ, Maugeri M, Mock CJ, Mok HY, Nordli Ø, Rodwell MJ, Ross TF, Schuster D, Srnec L, Valente MA, Vizi Z, Wang XL, Westcott N, Woollen JS, Worley SJ (2015) The International Surface Pressure Databank version 2. Geosci Data J 2:31–46.  https://doi.org/10.1002/gdj3.25 CrossRefGoogle Scholar
  15. de Boisseson E, Balmaseda MA, Mayer M (2017) Ocean het content variability in an ensemble of twentieth century ocean reanalyses. Clim Dyn.  https://doi.org/10.1007/s00382-017-3845-0 Google Scholar
  16. Dee DP, Uppala SM, Simmons AJ, Berrisford P, Poli P, Kobayashi S, Andrae U, Balmaseda MA, Balsamo G, Bauer P, Bechtold P, Beljaars ACM, van de Berg L, Bidlot J, Bormann N, Delsol C, Dragani R, Fuentes M, Geer AJ, Haimberger L, Healy SB, Hersbach H, Hólm EV, Isaksen L, Kållberg P, Köhler M, Matricardi M, McNally AP, Monge-Sanz BM, Morcrette J-J, Park B-K, Peubey C, de Rosnay P, Tavolato C, Thépaut J-N, Vitart F (2011) The ERA-Interim reanalysis: configuration and performance of the data assimilation system. QJR Meteorol Soc 137:553–597.  https://doi.org/10.1002/qj.828 CrossRefGoogle Scholar
  17. Desroziers G, Berre L, Chapnik B, Poli P (2005) Diagnosis of observation, background and analysis-error statistics in observation space. QJR Meteorol Soc 131:3385–3396.  https://doi.org/10.1256/qj.05.108 CrossRefGoogle Scholar
  18. Ferguson CR, Villarini G (2014) An evaluation of the statistical homogeneity of the Twentieth Century Reanalysis. Clim Dyn 42(11–12):2841–2866CrossRefGoogle Scholar
  19. Freeman E et al (2016) ICOADS Release 3.0: A major update to the historical marine 626 climate record. Int J Climatol.  https://doi.org/10.1002/joc.4775 Google Scholar
  20. Giese BS, Seidel HF, Compo GP, Sardeshmukh PD (2016) An ensemble of ocean reanalyses for 1815–2013 with sparse observational input. J Geophys Res Oceans 121:6891–6910CrossRefGoogle Scholar
  21. Good SA, Martin MJ, Rayner NA (2013) EN4: quality controlled ocean temperature and salinity profiles and monthly objective analyses with uncertainty estimates. J Geophys Res Oceans 118:6704–6716.  https://doi.org/10.1002/2013JC009067 CrossRefGoogle Scholar
  22. Gouretski V, Reseghetti F (2010) On depth and temperature biases in bathythermograph data: development of a new correction scheme based on analysis of a global ocean database. Deep-Sea Res I 57:6.  https://doi.org/10.1016/j.dsr.2010.03.011 CrossRefGoogle Scholar
  23. Griffin RE (2015) When are old data new data? Geo Res J 6:92–97.  https://doi.org/10.1016/j.grj.2015.02.004 Google Scholar
  24. Hersbach H, Peubey C, Simmons A, Berrisford P, Poli P, Dee D (2015) ERA-20CM: a twentieth-century atmospheric model ensemble. QJR Meteorol Soc 141:2350–2375.  https://doi.org/10.1002/qj.2528 CrossRefGoogle Scholar
  25. Hersbach H, Brönnimann S, Haimberger L, Mayer M, Villiger L, Comeaux J, Simmons A, Dee D, Jourdain S, Peubey C, Poli P, Rayner N, Sterin AM, Stickler A, Valente MA, Worley SJ (2017) The potential value of early (1939–1967) upper-air data in atmospheric climate reanalysis. QJR Meteorol Soc 143:1197–1210.  https://doi.org/10.1002/qj.3040 CrossRefGoogle Scholar
  26. Ishii M, Kimoto M (2009) Reevaluation of historical ocean heat variations with time-varying XBT and MBT depth bias correction. J Oceanogr 65:287–299.  https://doi.org/10.1007/s10872-009-0027-7 CrossRefGoogle Scholar
  27. Kalnay E et al (1996) The NCEP/NCAR 40-Year Reanalysis Project. Bull Am Meteorol Soc 77:437–471CrossRefGoogle Scholar
  28. Kato S, Loeb NG, Rose FG, Doelling DR, Rutan DA, Caldwell TE, Yu L, Weller RA (2013) Surface irradiances consistent with CERES-derived top-of-atmosphere shortwave and longwave irradiances. J Clim 26:2719–2740CrossRefGoogle Scholar
  29. Kennedy JJ (2014) A review of uncertainty in in situ measurements and data sets of sea surface temperature. Rev Geophys 52:1–32.  https://doi.org/10.1002/2013RG000434 CrossRefGoogle Scholar
  30. Kent EC, Fangohr S, Berry DI (2013) A comparative assessment of monthly mean wind speed products over the global ocean. Int J Climatol 33:2520–2541.  https://doi.org/10.1002/joc.3606 CrossRefGoogle Scholar
  31. Laloyaux P, Balmaseda M, Dee D, Mogensen K, Janssen P (2016) A coupled data assimilation system for climate reanalysis. QJR Meteorol Soc 142:65–78.  https://doi.org/10.1002/qj.2629 CrossRefGoogle Scholar
  32. Laloyaux P, de Boisseson E, Balmasdea M, Bidlot J-R, Broennimann S, Buizza R, Dalhgren P, Dee D, Haiberger L, Hersbach H, Kosaka Y, Martin M, Poli P, Rayner N, Rustemeier E, Schepers D (2018) CERA-20C: a coupled reanalysis of the Twentieth Century. J Adv Modell Earth Syst.  https://doi.org/10.1029/2018MS001273 Google Scholar
  33. Large W, Yeager S (2004) Diurnal to decadal global forcing for ocean and seaice models: the data sets and climatologies. Technical Report TN-460 + STR, NCARGoogle Scholar
  34. Lindsay R, Wensnahan M, Schweiger A, Zhang J (2014) Evaluation of seven different atmospheric reanalysis products in the arctic. J Clim 27:2588–2606.  https://doi.org/10.1175/JCLI-D-13-00014.1 CrossRefGoogle Scholar
  35. Madec G, the NEMO team (2012) “NEMO ocean engine”. Note du Pole de modélisation de l’Institut Pierre-Simon Laplace, France, No 27 ISSN No 1288–1619Google Scholar
  36. Masina S, Storto A (2017) Reconstructing the recent past ocean variability: status and perspective. J Mar Sci 75:727–764.  https://doi.org/10.1357/002224017823523973 Google Scholar
  37. Paek H, Huang H (2012) A comparison of decadal-to-interdecadal variability and trend in reanalysis datasets using atmospheric angular momentum. J Clim 25:4750–4758.  https://doi.org/10.1175/JCLI-D-11-00358.1 CrossRefGoogle Scholar
  38. Penny SG, Behringer DW, Carton JA, Kalnay E (2015) A hybrid global ocean data assimilation system at NCEP. Mon Weather Rev 143:4660–4677.  https://doi.org/10.1175/MWR-D-14-00376.1 CrossRefGoogle Scholar
  39. Poli P et al (2013) The data assimilation system and initial performance evaluation of the ECMWF pilot reanalysis of the 20th-century assimilating surface observations only (ERA-20C). ECMWF ERA Rep 14:59. http://www.ecmwf.int/en/elibrary/11699-data-assimilation-system-and-initial-performance-evaluation-ecmwf-pilot-reanalysis
  40. Poli P, Hersbach H, Berrisford P, Dee D, Simmons A, Laloyaux P (2015) ERA-20C deterministic. ECMWF ERA Rep 20:48. http://www.ecmwf.int/en/elibrary/11700-era-20c-deterministic
  41. Poli P, Hersbach H, Dee DP, Berrisford P, Simmons AJ, Vitart F, Laloyaux P, Tan DH, Peubey C, Thépaut J, Trémolet Y, Hólm EV, Bonavita M, Isaksen L, Fisher M (2016) ERA-20C: an atmospheric reanalysis of the Twentieth Century. J Clim 29:4083–4097.  https://doi.org/10.1175/JCLI-D-15-0556.1 CrossRefGoogle Scholar
  42. Rayner NA, Parker DE, Horton EB, Folland CK, Alexander LV, Rowell DP, Kent EC, Kaplan A (2003) Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century J Geophys Res 108(D14):4407.  https://doi.org/10.1029/2002JD002670 CrossRefGoogle Scholar
  43. Robock A (2000) Volcanic eruptions and climate. Rev Geophys 38:191–219.  https://doi.org/10.1029/1998RG000054 CrossRefGoogle Scholar
  44. Smith DM, Murphy JM (2007) An objective ocean temperature and salinity analysis using covariances from a global climate model. J Geophys Res 112:C02022.  https://doi.org/10.1029/2005JC003172 CrossRefGoogle Scholar
  45. Sterl A (2004) On the (In)Homogeneity of reanalysis products. J Clim 17:3866–3873.  https://doi.org/10.1175/1520-0442(2004)017%3C3866:OTIORP%3E2.0.CO;2 CrossRefGoogle Scholar
  46. 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
  47. Storto A, Masina S, Dobricic S (2014) Estimation and impact of non-uniform horizontal correlation length-scales for global ocean physical analyses. J Atmos Ocean Tech 31:2330–2349CrossRefGoogle Scholar
  48. Storto A, Yang C, Masina S (2016), Sensitivity of global ocean heat content from reanalyses to the atmospheric reanalysis forcing: A comparative study, Geophys Res Lett.  https://doi.org/10.1002/2016GL068605 Google Scholar
  49. Taylor K, Stouffer R, Meehl G (2012) An overview of CMIP5 and the experiment design. Bull Am Meteorol Soc 93:485–498.  https://doi.org/10.1175/BAMS-D-11-00094.1 CrossRefGoogle Scholar
  50. Thorne PW, Allan RJ, Ashcroft L, Brohan P, Dunn RJ, Menne MJ, Pearce PR, Picas J, Willett KM, Benoy M, Bronnimann S, Canziani PO, Coll J, Crouthamel R, Compo GP, Cuppett D, Curley M, Duffy C, Gillespie I, Guijarro J, Jourdain S, Kent EC, Kubota H, Legg TP, Li Q, Matsumoto J, Murphy C, Rayner NA, Rennie JJ, Rustemeier E, Slivinski LC, Slonosky V, Squintu A, Tinz B, Valente MA, Walsh S, Wang XL, Westcott N, Wood K, Woodruff SD, Worley SJ (2017) Towards an integrated set of surface meteorological observations for climate science and applications. Bull Am Meteorol Soc.  https://doi.org/10.1175/BAMS-D-16-0165.1 Google Scholar
  51. Titchner HA, Rayner NA (2014) The Met Office Hadley Centre sea ice and sea-surface temperature data set, version 2: 1. Sea ice concentrations. J Geophys Res 119:2864–2889.  https://doi.org/10.1002/2013JD020316 Google Scholar
  52. Trenberth KE, Fasullo JT, Balmaseda M (2014) Earth’s energy imbalance. J Clim 27:3129–3144CrossRefGoogle Scholar
  53. Valdivieso M et al (2015) An assessment of air–sea heat fluxes from ocean and coupled reanalyses. Clim Dyn.  https://doi.org/10.1007/s00382-015-2843-3 Google Scholar
  54. Vancoppenolle M, Fichefet T, Goosse H, Bouillon S, Madec G, Morales Maqueda MA (2009) Simulating the mass balance and salinity of Arctic and Antarctic sea ice. 1. Model description and validation. Ocean Model 27(1–2):33–53CrossRefGoogle Scholar
  55. Wang X, Feng Y, Chan R, Isaac V (2016) Inter-comparison of extra-tropical cyclone activity in nine reanalysis datasets. Atmos Res 181:133–153.  https://doi.org/10.1016/j.atmosres.2016.06.010. (ISSN 0169–8095)CrossRefGoogle Scholar
  56. Whitaker JS, Hamill TM (2002) Ensemble data assimilation without perturbed observations. Mon Weather Rev 130:1913–1924CrossRefGoogle Scholar
  57. Woodruff SD, Coauthors (2011) ICOADS release 2.5: Extensions and enhancements to the surface marine meteorological archive. Int J Climatol 31:951–967.  https://doi.org/10.1002/joc.2103 CrossRefGoogle Scholar
  58. Wu et al (2012) Enhanced warming over the global subtropical western boundary currents. Nat Clim Chang.  https://doi.org/10.1038/NCLIMATE1353 Google Scholar
  59. Yang C, Giese BS (2013) El Niño Southern Oscillation in an ensemble ocean reanalysis and coupled climate models. J Geophys Res Oceans 118(9):4052CrossRefGoogle Scholar
  60. Yang C, Masina S, Storto A (2017) Historical ocean reanalyses (1900–2010) using different data assimilation strategies. QJR Meteorol Soc 143:479–493.  https://doi.org/10.1002/qj.2936 CrossRefGoogle Scholar
  61. Yi DL, Zhang L, Wu L (2015) On the mechanisms of decadal variability of the North Pacific Gyre Oscillation over the 20th century. J Geophys Res Oceans 120:6114–6129.  https://doi.org/10.1002/2014JC010660 CrossRefGoogle Scholar
  62. Zib B, Dong X, Xi B, Kennedy A (2012) Evaluation and intercomparison of cloud fraction and radiative fluxes in recent reanalyses over the Arctic using BSRN surface observations. J Clim 25:2291–2305.  https://doi.org/10.1175/JCLI-D-11-00147.1 CrossRefGoogle Scholar

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© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Institute of Atmospheric Sciences and ClimateNational Research Council (CNR-ISAC)RomeItaly
  2. 2.Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici (CMCC)BolognaItaly
  3. 3.Istituto Nazionale di Geofisica e Vulcanologia (INGV)Sezione di BolognaBolognaItaly

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