4.6 Article

Assessment of South America summer rainfall climatology and trends in a set of global climate models large ensembles

Journal

INTERNATIONAL JOURNAL OF CLIMATOLOGY
Volume 41, Issue -, Pages E59-E77

Publisher

WILEY
DOI: 10.1002/joc.6643

Keywords

climate change; large ensembles; model evaluation; precipitation trends; South America

Funding

  1. CLIMAX Project/Belmont Forum [ANR-15-JCL/-0002-01]
  2. Fondo para la Investigacion Cientifica y Tecnologica [PICT 1898-2016]
  3. Universidad de Buenos Aires [UBACyT20020170100428BA]

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This study assesses the ability of a set of Global Climate Model simulations in reproducing the variability and change of austral summer precipitation observed in South America, indicating that models still have biases and uncertainties in representing the trends and variability of rainfall in the region. Further improvements are needed to reduce uncertainties associated with main climate change signals in the continent.
The purpose of this study is to assess the ability of a set of large ensembles (LE) of Global Climate Model (GCM) simulations from the Multi-Model Large Ensemble Archive, Coupled Model Intercomparison Project Phase 6 (CMIP6) and database for Policy Decision making for Future climate change in reproducing the variability and change of the austral summer precipitation observed in South America along the second part of the 20th century and beginning of the 21st. LE show similar biases in the mean austral summer rainfall and interannual variability than those detected in previous model sets, such as the Coupled Model Intercomparison Project Phase 5 (CMIP5). The positive trends in south-eastern South America (SESA) and negative ones in the southern Andes (SAn), that are the most significant observed regional features, are identified to some extent in LE simulations. The negative trend in SAn is a feature consistently shown among different models. For all models, mean trend is negative in that particular region and larger than the inter-member dispersion for each large ensemble. Trend magnitudes in the SESA region show a larger dispersion between models than the SAn region. While the mean trend among models is consistent with the observations, models underestimate the observed trend. The multi-model ensemble of selected models that best reproduce both mean and interannual variability features of rainfall in South America shows an 18% larger positive mean trend in SESA rainfall than those that have the worst performance. However, internal variability uncertainty is still higher than the mean trend for both sets of multi-model ensembles [5% (18%) for selected (non-selected) models]. Improvements in the representation of the main features of mean rainfall and variability are needed in order to better describe and reduce the uncertainties associated with the main climate change related signals in the continent.

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