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

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.

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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

    Article  Google 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

    Article  Google 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 69:39–49

    Article  Google 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 29:575–590

    Article  Google 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-MER

  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, DC

    Google 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 29:4817–4842

    Article  Google 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

    Article  Google 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

    Article  Google 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

    Article  Google 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

    Article  Google 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

    Article  Google 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

    Article  Google 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

    Article  Google Scholar 

  18. Ferguson CR, Villarini G (2014) An evaluation of the statistical homogeneity of the Twentieth Century Reanalysis. Clim Dyn 42(11–12):2841–2866

    Article  Google 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 121:6891–6910

    Article  Google 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

    Article  Google 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

    Article  Google 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

    Article  Google 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

    Article  Google 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

    Article  Google Scholar 

  27. Kalnay E et al (1996) The NCEP/NCAR 40-Year Reanalysis Project. Bull Am Meteorol Soc 77:437–471

    Article  Google 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 26:2719–2740

    Article  Google 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

    Article  Google 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

    Article  Google 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

    Article  Google 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, NCAR

  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

    Article  Google 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 1288–1619

  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

    Article  Google 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

    Article  Google 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

    Article  Google 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

    Article  Google Scholar 

  43. Robock A (2000) Volcanic eruptions and climate. Rev Geophys 38:191–219. https://doi.org/10.1029/1998RG000054

    Article  Google 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

    Article  Google 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

    Article  Google 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 139:738–754

    Article  Google 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 31:2330–2349

    Article  Google 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

    Article  Google 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 27:3129–3144

    Article  Google 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):33–53

    Article  Google 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)

    Article  Google Scholar 

  56. Whitaker JS, Hamill TM (2002) Ensemble data assimilation without perturbed observations. Mon Weather Rev 130:1913–1924

    Article  Google 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

    Article  Google 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):4052

    Article  Google 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

    Article  Google 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

    Article  Google 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

    Article  Google Scholar 

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Acknowledgements

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

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Correspondence to Chunxue Yang.

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Yang, C., Storto, A. & Masina, S. Quantifying the effects of observational constraints and uncertainty in atmospheric forcing on historical ocean reanalyses. Clim Dyn 52, 3321–3342 (2019). https://doi.org/10.1007/s00382-018-4331-z

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Keywords

  • Ocean Reanalysis
  • Ocean Heat Content (OHC)
  • Ocean Observation Network
  • Data Assimilation
  • Root Mean Square Deviation (RMSD)