Abstract
AbstractPrevious studies have revealed little progress in the ensemble mean of Coupled Model Intercomparison Project Phase 6 (CMIP6) models compared to Phase 5 (CMIP5) models in simulating global dynamic sea level (DSL). This study investigates the performance of the CMIP5 and CMIP6 ensembles in simulating the spatial pattern and magnitude of DSL climatology, seasonal variability, interannual variability, and decadal variability by using the pattern correlation coefficient (PCC) and root-mean-square error (RMSE) as metrics. We show that the top models of the CMIP6 ensemble perform better than those of the CMIP5 ensemble in the simulation of DSL climatology and seasonal and interannual variability, but not DSL decadal variability. An intermodel linear relationship between the RMSE and PCC is found for both the CMIP5 and CMIP6 ensembles; however, this intermodel relationship is more linearly correlated in the CMIP6 ensemble and not significant for DSL decadal variability. The results show that the finer-horizontal resolution models tend to yield a smaller RMSE and a larger PCC in the DSL climatology, seasonal variability, interannual variability but not decadal variability simulations, and the relationship is more evident for the CMIP6 ensemble than for the CMIP5 ensemble.
Funder
the National Key R&D Program for Developing Basic Sciences
the Strategic Priority Research Program of the Chinese Academy of Sciences
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
General Earth and Planetary Sciences
Reference34 articles.
1. Bellenger H, Guilyardi É, Leloup J et al (2014) ENSO: representation in climate models from CMIP3 to CMIP5. Clim Dyn 42(7):1999–2018. https://doi.org/10.1007/s00382-013-1783-z
2. Bindoff NL, Willebrand J, Artale V et al (2007) Observations: oceanic climate change and sea level. In: Solomon S (ed) Climate change 2007: the physical science basis, vol 4. University Press, Cambridge, pp 386–432
3. Church JA, White NJ (2006) A 20th century acceleration in global sea-level rise. Geophys Res lett. https://doi.org/10.1029/2005GL024826
4. Ericson JP, Vörösmarty CJ, Dingman SL et al (2006) Effective sea-level rise and deltas: causes of change and human dimension implications. Global Planet Change 50(1–2):63–82. https://doi.org/10.1016/j.gloplacha.2005.07.004
5. Fasullo JT, Phillips AS, Deser C (2020) Evaluation of leading modes of climate variability in the CMIP archives. J Clim 33(13):5527–5545. https://doi.org/10.1175/JCLI-D-19-1024.1