Abstract
We present an unprecedented ensemble of 196 future climate projections arising from different global and regional model intercomparison projects (MIPs): CMIP3, CMIP5, ENSEMBLES, ESCENA, EURO- and Med-CORDEX. This multi-MIP ensemble includes all regional climate model (RCM) projections publicly available to date, along with their driving global climate models (GCMs). We illustrate consistent and conflicting messages using continental Spain and the Balearic Islands as target region. The study considers near future (2021–2050) changes and their dependence on several uncertainty sources sampled in the multi-MIP ensemble: GCM, future scenario, internal variability, RCM, and spatial resolution. This initial work focuses on mean seasonal precipitation and temperature changes. The results show that the potential GCM–RCM combinations have been explored very unevenly, with favoured GCMs and large ensembles of a few RCMs that do not respond to any ensemble design. Therefore, the grand-ensemble is weighted towards a few models. The selection of a balanced, credible sub-ensemble is challenged in this study by illustrating several conflicting responses between the RCM and its driving GCM and among different RCMs. Sub-ensembles from different initiatives are dominated by different uncertainty sources, being the driving GCM the main contributor to uncertainty in the grand-ensemble. For this analysis of the near future changes, the emission scenario does not lead to a strong uncertainty. Despite the extra computational effort, for mean seasonal changes, the increase in resolution does not lead to important changes.
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Acknowledgements
Authors are grateful to the modelling groups from the Euro-CORDEX, Med-CORDEX, CMIP3 and CMIP5 initiatives and the ENSEMBLES project. We also thank the ESGF and CERA for data provision and R and CDO developers for providing free libraries and data operators. This work has been funded by the Spanish R+D Program of the Ministry of Environment and Rural and Marine Affairs through ESCENA project (200800050084265) and the Ministry of Economy and Competitiveness, through grants MULTI-SDM (CGL2015-66583-R) and INSIGNIA (CGL2016-79210-R), co-funded by ERDF/FEDER. A.S.C. acknowledges support from the EU-funded FP7 project IS-ENES2 (GA 312979). Universidad de Cantabria simulations have been carried out on the Altamira Supercomputer at the Instituto de Física de Cantabria (IFCA-CSIC), member of the Spanish Supercomputing Network.
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382_2018_4181_MOESM1_ESM.pdf
Precipitation vs mean surface temperature JJA delta changes spatially averaged over Continental Spain and the Balearic Islands for each ensemble member. (a) Deltas for the 196-member ensemble. (b) Deltas by Project. (c) Deltas by Resolution. (d) Deltas by Scenario. (e) Deltas by GCM Family. (f) Deltas by Method. Marginal probability density functions are shown for each variable pooling the whole 196-member ensemble for the different classification, using a Gaussian kernel density estimator. Tickmarks show the ranges from the 5th to 95th percentile (90\% of the sample) and from the 1st to 3rd quartile (50\%). The median is also shown as an inner tickmark (thicker). Raw GCM output deltas are shown as empty circles (PDF 377 KB)
382_2018_4181_MOESM2_ESM.pdf
Precipitation vs mean surface temperature delta changes spatially averaged over Continental Spain and the Balearic Islands for each ensemble member. Values classified by project. (a) DJF. (b) MAM. (c) JJA. (d) SON. Marginal probability density functions are shown for each variable and project pooling the whole 196-member ensemble, using a Gaussian kernel density estimator. Tickmarks show the ranges from the 5th to 95th percentile (90\% of the sample) and from the 1st to 3rd quartile (50\%). The median is also shown as a thicker inner tickmark. (PDF 241 KB)
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Fernández, J., Frías, M.D., Cabos, W.D. et al. Consistency of climate change projections from multiple global and regional model intercomparison projects. Clim Dyn 52, 1139–1156 (2019). https://doi.org/10.1007/s00382-018-4181-8
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DOI: https://doi.org/10.1007/s00382-018-4181-8