Journal of Ocean University of China

, Volume 17, Issue 2, pp 209–218 | Cite as

Intercomparison of the Extended Reconstructed Sea Surface Temperature v4 and v3b Datasets

  • Jinping Wang
  • Xianyao ChenEmail author


Version 4 (v4) of the Extended Reconstructed Sea Surface Temperature (ERSST) dataset is compared with its precedent, the widely used version 3b (v3b). The essential upgrades applied to v4 lead to remarkable differences in the characteristics of the sea surface temperature (SST) anomaly (SSTa) in both the temporal and spatial domains. First, the largest discrepancy of the global mean SSTa values around the 1940s is due to ship-observation corrections made to reconcile observations from buckets and engine intake thermometers. Second, differences in global and regional mean SSTa values between v4 and v3b exhibit a downward trend (around −0.032°C per decade) before the 1940s, an upward trend (around 0.014°C per decade) during the period of 1950–2015, interdecadal oscillation with one peak around the 1980s, and two troughs during the 1960s and 2000s, respectively. This does not derive from treatments of the polar or the other data-void regions, since the difference of the SSTa does not share the common features. Third, the spatial pattern of the ENSO-related variability of v4 exhibits a wider but weaker cold tongue in the tropical region of the Pacific Ocean compared with that of v3b, which could be attributed to differences in gap-filling assumptions since the latter features satellite observations whereas the former features in situ ones. This intercomparison confirms that the structural uncertainty arising from underlying assumptions on the treatment of diverse SST observations even in the same SST product family is the main source of significant SST differences in the temporal domain. Why this uncertainty introduces artificial decadal oscillations remains unknown.


ERSST datasets sea surface temperature global warming Arctic data intercomparison 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.



We like to thank Boyin Huang and Thomas Karl for helpful comments. The work was supported by the National Key Basic Research and Development Plan (No. 2015CB953900), and the Natural Science Foundation of China (Nos. 41330960 and 41776032).


  1. Bretherton, C. S., Widmann, M., Dymnidov, V. P., Wallace, J. M., and Blade, I., 1999. The effective number of spatial degrees of freedom of a time-varying field. Journal of Climate, 12: 1990–2009.CrossRefGoogle Scholar
  2. Chen, X., and Wallace, J. M., 2015. ENSO-like variability: 1900–2013. Journal of Climate, 28: 9623–9641, DOI: 10.1175/JCLI-D-15-0322.1.CrossRefGoogle Scholar
  3. Cowtan, K., and Way, R. G., 2014. Coverage bias in the Had-CRUT4 temperature series and its impact on recent temperature trends. Quarterly Journal of the Royal Meteorological Society, 140: 1935–1944, DOI: 10.1002/qj.2297.CrossRefGoogle Scholar
  4. Ding, Q., Steig, E. J., Battisti, D. S., and Wallace, J. M., 2012. Influence of the tropics on the Southern Annular Mode. Journal of Climate, 25: 6330–6348, DOI: 10.1175/JCLI-D-11-00523.1.CrossRefGoogle Scholar
  5. Enfield, D. B., Mestas-Nuñez, A. M., and Trimble, P. J., 2001. The Atlantic multidecadal oscillation and its relation to rainfall and river flows in the continental U.S. Geophysical Research Letters, 28: 2077–2080.CrossRefGoogle Scholar
  6. Folland, C. K., and Parker, D. E., 1995. Correction of instrumental biases in historical sea surface temperature data. Quarterly Journal of the Royal Meteorological Society, 121: 319–367, DOI: 10.1002/qj.49712152206.CrossRefGoogle Scholar
  7. Folland, C. K., Colman, A. W., Smith, D. M., Boucher, O., Parker, D. E., and Vernier, J. P., 2013. High predictive skill of global surface temperature a year ahead. Geophysical Research Letters, 40: 761–767, DOI: 10.1002/grl.50169.CrossRefGoogle Scholar
  8. Fyfe, J. C., Meehl, G. A., England, M. H., Mann, M. E., Santer, B. D., Flato, G. M., Hawkins, E. N., Gillett, P., Xie, S., Kosaka, Y., and Swart, N. C., 2016. Making sense of the early-2000s warming slowdown. Nature Climate Change, 6: 224–228, DOI: 10.1038/nclimate2938.CrossRefGoogle Scholar
  9. Held, I. M., 2013. The cause of the pause. Nature, 501: 318–319, DOI: 10.1038/501318a.CrossRefGoogle Scholar
  10. Hirahara, S., Ishii, M., and Fukuda, Y., 2014. Centennial-scale sea surface temperature analysis and its uncertainty. Journal of Climate, 27: 57–75, DOI: 10.1175/JCLI-D-12-00837.1.CrossRefGoogle Scholar
  11. Huang, B., Banzon, V. F., Freeman, E., Lawrimore, J., Liu, W., Peterson, T. C., Smith, T. M., Thorne, P. W., Woodruff, S. D., and Zhang, H. M., 2015a. Extended reconstructed sea surface temperature version 4 (ERSST.v4), Part I. Upgrades and intercomparisons. Journal of Climate, 28: 911–930, DOI: 10.1175/JCLI-D-14-00006.1.CrossRefGoogle Scholar
  12. Huang, B., Wang, W., Liu, C., Banzon, V., Zhang, H., and Lawrimore, J., 2015b. Bias adjustment of AVHRR SST and its impacts on two SST analyses. Journal of Atmospheric & Oceanic Technology, 32: 372–387, DOI: 10.1175/JTECH-D-14-00121.1.CrossRefGoogle Scholar
  13. Kaplan, A., Cane, M. A., Kushnir, Y., Clement, A. C., Blumen thal, M. B., and Rajagopalan, B., 1998. Analyses of global sea surface temperature 1856–1991. Geophysical Research Letters, 103: 18567–18589, DOI: 10.1029/97JC01736.CrossRefGoogle Scholar
  14. Karl, T. R., Arguez, A., Huang, B., Lawrimore, J. H., McMahon, J. R., Menne, M. J., Peterson, T. C., Vose, R. S., and Zhang, H. M., 2015. Possible artifacts of data biases in the recent global surface warming hiatus. Science, 348: 1469–1472, DOI: 10.1126/science.aaa5632.CrossRefGoogle Scholar
  15. Kennedy, J. J., 2014. A review of uncertainty in in situ measurements and data sets of sea surface temperature. Reviews of Geophysics, 52: 1–32, DOI: 10.1002/2013RG000434.CrossRefGoogle Scholar
  16. Kennedy, J. J., Rayner, N. A., Smith, R. O., Parker, D. E., and Saunby, M., 2011a. Reassessing biases and other uncertainties in sea surface temperature observations measured in situ since 1850: 1. Measurement and sampling uncertainties. Journal of Geophysical Research Atmospheres, 116: D14103, DOI: 10.1029/2010JD015218.CrossRefGoogle Scholar
  17. Kennedy, J. J., Rayner, N. A., Smith, R. O., Parker, D. E., and Saunby, M., 2011b. Reassessing biases and other uncertainties in sea surface temperature observations measured in situ since 1850: 2. Biases and homogenization. Journal of Geophysical Research Atmospheres, 116: D14104, DOI: 10.1029/2010JD015220.CrossRefGoogle Scholar
  18. Kent, E. C., Kennedy, J. J., Berry, D. I., and Smith, R. O., 2010. Effects of instrumentation changes on sea surface temperature measured in situ. Climatic Change, 1: 718–728, DOI: 10.1002/wcc.55.Google Scholar
  19. Lewandowsky, S., Oreskes, N., Risbey, J. S., Newell, B. R., and Smithson, M., 2015. Seepage: Climate change denial and its effect on the scientific community. Global Environmental Change, 33: 1–13, DOI: 10.1016/j.gloenvcha.2015.02.013.CrossRefGoogle Scholar
  20. Liu, W., Huang, B., Thorne, P. W., Banzon, V. F., Zhang, H.-M., Freeman, E., Lawrimore, J., Peterson, T. C., Smith, T. M., and Woodruff, S. D., 2015. Extended reconstructed sea surface temperature version 4 (ERSST.v4), part II: Parametric and structural uncertainty estimation. Journal of Climate, 28: 931–951, DOI: 10.1175/JCLI-D-14-00007.1.CrossRefGoogle Scholar
  21. Rayner, N. A., Parker, D. E., Horton, E. B., Folland, C. K., Alexander, L. V., Rowell, D. P., Kent, E. C., and Kaplan, A., 2003. Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. Journal of Geophysical Research, 108: 4407, DOI: 10.1029/2002JD002670.CrossRefGoogle Scholar
  22. Rayner, N., Brohan, P., Parker, D., Folland, C., Kennedy, J., Vanicek, M., Ansell, T., and Tett, S., 2006. Improved analyses of changes and uncertainties in sea surface temperature measured in situ since the mid-nineteenth century: The HadSST2 data set. Journal of Climate, 19: 446–469, DOI: 10.1175/JCLI3637.1.CrossRefGoogle Scholar
  23. Reynolds, R. W., Gentemann, C. L., and Corlett, G. K., 2010. Evaluation of AATSR and TMI satellite SST data. Journal of Climate, 23: 152–165, DOI: 10.1175/2009JCLI3252.1.CrossRefGoogle Scholar
  24. Reynolds, R. W., Rayner, N. A., Smith, T. M., Stokes, D. C., and Wang, W., 2002. An improved in situ and satellite SST analysis for climate. Journal of Climate, 15: 1609–1625, DOI: 10.1175/1520-0442(2002)015,1609:AIISAS.2.0.CO;2.CrossRefGoogle Scholar
  25. Saji, N. H., Goswami, B. N., Vinayachandran, P. N., and Yamagata, T., 1999. A dipole mode in the tropical Indian Ocean. Nature, 401: 360–363.Google Scholar
  26. Schlesinger, M. E., and Ramankutty, N., 1994. An oscillation in the global climate system of period 65–70 years. Nature, 367: 723–726, DOI: 10.1038/367723a0.CrossRefGoogle Scholar
  27. Simmons, A. J., Willett, K. M., Jones, P. D., Thorne, P. W., and Dee, D. P., 2010. Low-frequency variations in surface atmospheric humidity, temperature, and precipitation: Inferences from reanalyses and monthly gridded observational data sets. Journal of Geophysical Research, 115: D01110, DOI: 10.1029/2009JD012442.Google Scholar
  28. Smith, T. M., and Reynolds, R. W., 2003. Extended reconstruction of global sea surface temperature based on COADS data (1854–1997). Journal of Climate, 16: 1495–1510, DOI: 10.1175/1520-0442-16.10.1495.CrossRefGoogle Scholar
  29. Smith, T. M., and Reynolds, R. W., 2004. Improved extended reconstruction of SST (1854–1997). Journal of Climate, 17: 2466–2477.CrossRefGoogle Scholar
  30. Smith, T. M., Reynolds, R. W., Peterson, T. C., and Lawrimore, J., 2008. Improvements to NOAA’s historical merged land–ocean surface temperature analysis (1880–2006). Journal of Climate, 21: 2283–2296, DOI: 10.1175/2007JCLI2100.1.CrossRefGoogle Scholar
  31. Thompson, D. W., Kennedy, J. J., Wallace, J. M., and Jones, P. D., 2008. A large discontinuity in the mid-20th century in observed global-mean surface temperature. Nature, 453: 646–649, DOI: 10.1038/nature06982.CrossRefGoogle Scholar
  32. Trenberth, K. E., and Shea, D. J., 2006. Atlantic hurricanes and natural variability in 2006. Geophysical Research Letters, 33: 285–293, DOI: 10.1029/2006GL026894.CrossRefGoogle Scholar
  33. van den Dool, H. M., Saha, S., and Johansson, A., 2000. Empirical orthogonal teleconnections. Journal of Climate, 13: 1421–1435.CrossRefGoogle Scholar
  34. Woodruff, S. D., Worley, S. J., Lubker, S. J., Ji, Z., Freeman, J. E., Berry, D. I., Brohan, P., Kent, E. C., Reynolds, R. W., Smith, S. R., and Wilkinson, C., 2011. ICOADS Release 2.5: Extensions and enhancements to the surface marine meteorological archive. International Journal of Climatology, 31: 951–967, DOI: 10.1002/joc.2103.CrossRefGoogle Scholar
  35. Zhang, Y., Wallace, J. M., and Battisti, D. S., 1997. ENSO-like decade-to-century scale variability. Journal of Climate, 10: 1004–1020.CrossRefGoogle Scholar

Copyright information

© Science Press, Ocean University of China and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Oceanography, College of Oceanic and Atmospheric SciencesOcean University of ChinaQingdaoChina
  2. 2.Physical Oceanography Laboratory/CIMSTOcean University of China and Qingdao National Laboratory for Marine Science and TechnologyQingdaoChina

Personalised recommendations