Cardoso, A.A., Mindlin, J., Coppola, E. and Shepherd, T.G.
ORCID: https://orcid.org/0000-0002-6631-9968
(2025)
A storyline approach to select the CMIP6 model ensemble to be downscaled for the South America domain.
Climate Dynamics.
ISSN 0930-7575
(In Press)
Abstract/Summary
Selecting the most appropriate Global Climate Models (GCMs) is necessary for Regional Climate Models (RCMs) downscaling. We propose a methodology to select CMIP6 GCMs based on the representation of the multiple physical processes which control regional circulation in a specific domain and the uncertainty in the precipitation projections. To develop the methodology, we identified relevant climate features for the South American (SA) region, focusing on the two most important climatological features: the South American Monsoon System (SAMS) and extratropical cyclones. A set of indicators was defined based on the precipitation in three specific regions (La Plata, the Amazon basins, and Southeastern Brazil) and circulation patterns that are part of the SAMS and control the trajectories of extratropical cyclones (South American Low-Level jets, South Atlantic and South Pacific Subtropical Highs, trade winds, Bolivian High, cyclonic vortices, and upper-level jet stream). The selection of the CMIP6 GCM ensemble is based on historical validation of the circulation patterns and the spread in possible future circulation changes that can lead to different precipitation responses. We used a storyline approach to assess the spread in the precipitation response controlled by regional circulation uncertainty and to identify the wettest and driest possible futures. To assess both SAMS (in summer) and extratropical cyclone patterns (in summer and winter), three storylines were used. The final proposed minimal ensemble comprises four CMIP6 GCMs that correctly represent the main climatological features in SA and are able to cover the uncertainty in the future precipitation response in the three examined regions.
| Item Type | Article |
| URI | https://centaur.reading.ac.uk/id/eprint/127508 |
| Refereed | Yes |
| Divisions | Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology |
| Publisher | Springer |
| Download/View statistics | View download statistics for this item |
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