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Regional climate projections of daily extreme temperatures in Argentina applying statistical downscaling to CMIP5 and CMIP6 models

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Abstract

Argentina is a country with a variety of climates, where an increase in mean and extreme temperatures is currently on-going, demanding regional climate information to design and implement effective strategies for climate change adaptation. In this regard, the use of empirical statistical downscaling (ESD) procedures can help provide tailored climate information. In this work, a set of ESD models were tested and applied to generate plausible regional climate projections for daily maximum and minimum temperatures (Tx, Tn) in Argentina. ESD models were applied to an ensemble of CMIP5 and CMIP6 global circulation models (GCMs) to downscale historical and future RCP8.5 and SSP585 scenarios. The plausibility of the ESD projections was analysed by comparing them with their driving GCMs and with CORDEX regional climate models (RCMs). Generally, all ESD models added value during the historical period, in mean values as well as in extreme indices, especially for Tx. The climate projections depicted an extended signal of warming (both in the mean and in the frequency of extremes), consistent between all simulations (GCMs, RCMs and ESD) and strongest over northern Argentina. ESD models showed potential to produce plausible projections, although, depending on the technique considered (for Tx) and the predictor configurations (for Tn), differences in the change rates were identified. Nevertheless, the uncertainty in future changes was considerably reduced by RCMs and ESD when compared to their driving GCMs. Overall, this study evidences the potential of ESD in a climate change context and contributes to the assessment of the uncertainty on the future Argentine climate.

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Availability of data and materials

The gridded datasets used in this study are available online. ERA-Interim reanalysis (Dee et al. 2011) https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era-interim. Simulations from CMIP5 and CMIP6 modelling experiment (Taylor et al. 2012; Eyring et al. 2016) https://esgf-node.llnl.gov. Station data was provided by the National Weather Service of Argentina, and can be acquired to be used for research purposes through the website https://www.smn.gob.ar.

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Funding

This work was supported by the University of Buenos Aires 20020220200111BA and the ANPCyT PICT-2018-02496 and PICT 2019-02933 projects.

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Authors and Affiliations

  1. Departamento de Ciencias de la Atmósfera y los Océanos (DCAO), Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Intendente Güiraldes 2160, Ciudad Universitaria, C1428EGA, Buenos Aires, Argentina

    Rocío Balmaceda-Huarte & Maria Laura Bettolli

  2. Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina

    Rocío Balmaceda-Huarte & Maria Laura Bettolli

  3. Instituto Franco-Argentino de Estudios sobre el Clima y sus Impactos (IFAECI)-IRL 3351-CNRS-CONICET-IRD-UBA, Buenos Aires, Argentina

    Rocío Balmaceda-Huarte & Maria Laura Bettolli

  4. Barcelona Supercomputing Center, Barcelona, Spain

    Matias Ezequiel Olmo

Authors
  1. Rocío Balmaceda-Huarte
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  2. Matias Ezequiel Olmo
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  3. Maria Laura Bettolli
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Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Rocio Balmaceda-Huarte. The original draft was written by Rocio Balmaceda-Huarte and Matias Olmo, and all authors made substantial contributions. Supervision was performed by María Laura Bettolli. All authors read and approved the final manuscript.

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Correspondence to Rocío Balmaceda-Huarte.

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Balmaceda-Huarte, R., Olmo, M.E. & Bettolli, M.L. Regional climate projections of daily extreme temperatures in Argentina applying statistical downscaling to CMIP5 and CMIP6 models. Clim Dyn 62, 4997–5018 (2024). https://doi.org/10.1007/s00382-024-07147-9

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