EGU2020-7603
https://doi.org/10.5194/egusphere-egu2020-7603
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Broad consistency between observed and simulated trends in sea surface temperature patterns

Dirk Olonscheck, Maria Rugenstein, and Jochem Marotzke
Dirk Olonscheck et al.
  • Max Planck Institute for Meteorology, Ocean in the Earth System, Hamburg, Germany (dirk.olonscheck@mpimet.mpg.de)

A realistic representation of sea surface temperature (SST) patterns in climate models is important for constraining local climate change and estimates of climate sensitivity (Gregory et al, 2016; Zhou et al, 2016; Armour, 2017; Marvel et al, 2018; Andrews et al, 2018). However, it is debated whether global climate models are capable of simulating the observed local SST patterns (Zhou et al, 2016; Coats et al, 2017; Marvel et al, 2018; Kostov et al, 2018; Seager et al, 2019). Using seven single-model initial condition ensembles with 30-100 ensemble members and the two multi-model ensembles CMIP5 and CMIP6, we here show that observed and simulated regional trends in SST patterns are consistent when accounting for internal variability. Some individual ensemble members simulate SST trend patterns that resemble the observed patterns in large areas across different basis. We find that observed and simulated SST trends are also consistent in critical regions such as the Southern Ocean, the North Atlantic, and the equatorial Pacific east-to-west SST gradient. Observed regional trends that lie at the outer edge of the models' internal-variability range allow two non-exclusive interpretations: a) observed trends are unusual realizations of the Earth's possible behavior and/or b) the models are systematically biased but large local variability leads to some good matches with the observations. Furthermore, we find that the large internal variability influences the existing range of SST trends more strongly than differences in the model formulation or in the observational data set.

 

References:

Andrews, T., Gregory, J. M., Paynter, D., Silvers, L. G., Zhou, C., Mauritsen, T., Webb, M. J., Armour, K. C., Forster, P. M., & Titchner, H. (2018). Accounting for Changing Temperature Patterns Increases Historical Estimates of Climate Sensitivity. Geophysical Research Letters, 45 (16), 8490–8499.

Armour, K. C. (2017). Energy budget constraints on climate sensitivity in light of inconstant climate feedbacks. Nature Climate Change, 7, 331–335.

Coats, S., & Karnauskas, K. B. (2017). Are Simulated and Observed Twentieth Century Tropical Pacific Sea Surface Temperature Trends Significant Relative to Internal Variability? Geophysical Research Letters, 44 (19), 9928–9937.

Gregory, J. M., & Andrews, T. (2016). Variation in climate sensitivity and feedback parameters during the historical period. Geophysical Research Letters, 43 (8), 3911–3920.

Kostov, Y., Ferreira, D., Armour, K. C., & Marshall, J. (2018). Contributions of Greenhouse Gas Forcing and the Southern Annular Mode to Historical Southern Ocean Surface Temperature Trends. Geophysical Research Letters, 45 (2), 1086–1097.

Marvel, K., Pincus, R., Schmidt, G. A., & Miller, R. L. (2018). Internal Variability and Disequilibrium Confound Estimates of Climate Sensitivity From Observations. Geophysical Research Letters, 45 (3), 1595–1601.

Seager, R., Cane, M., Henderson, N., Lee, D.-E., Abernathey, R., & Zhang, H. (2019). Strengthening tropical Pacific zonal sea surface temperature gradient consistent with rising greenhouse gases. Nature Climate Change, 9 (7), 517–522.

Zhou, C., Zelinka, M. D., & Klein, S. A. (2016). Impact of decadal cloud variations on the Earth’s energy budget. Nature Geoscience, 9 (12), 871–874.

How to cite: Olonscheck, D., Rugenstein, M., and Marotzke, J.: Broad consistency between observed and simulated trends in sea surface temperature patterns, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7603, https://doi.org/10.5194/egusphere-egu2020-7603, 2020

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