The CORDEX Flagship Pilot Study in southeastern South America: a comparative study of statistical and dynamical downscaling models in simulating daily extreme precipitation events

Climate Dynamics (2021)Cite this article

Abstract

The aim of this work is to present preliminary results of the statistical and dynamical simulations carried out within the framework of the Flagship Pilot Study in southeastern South America (FPS-SESA) endorsed by the Coordinated Regional Climate Downscaling Experiments (CORDEX) program. The FPS-SESA initiative seeks to promote inter-institutional collaboration and further networking with focus on extreme rainfall events. The main scientific aim is to study multi-scale processes and interactions most conducive to extreme precipitation events through both statistical and dynamical downscaling techniques, including convection-permitting simulations. To this end, a targeted experiment was designed considering the season October 2009 to March 2010, a period with a record number of extreme precipitation events within SESA. Also, three individual extreme events within that season were chosen as case studies for analyzing specific regional processes and sensitivity to resolutions. Four dynamical and four statistical downscaling models (RCM and ESD respectively) from different institutions contributed to the experiment. In this work, an analysis of the capability of the set of the FPS-SESA downscaling methods in simulating daily precipitation during the selected warm season is presented together with an integrated assessment of multiple sources of observations and available CORDEX Regional Climate Model simulations. Comparisons among all simulations reveal that there is no single model that performs best in all aspects evaluated. The ability in reproducing the different features of daily precipitation depends on the model. However, the evaluation of the sequence of precipitation events, their intensity and timing suggests that FPS-SESA simulations based on both RCM and ESD yield promising results. Most models capture the extreme events selected, although with a considerable spread in accumulated values and the location of heavy precipitation.

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Acknowledgements

Thanks to CORDEX for endorsing the FPS-SESA. This work was supported by the University of Buenos Aires 2018-20020170100117BA grant; JMG, MLB, SAS, RPR funding from the Spanish Research Council (CSIC) I-COOP+ Program “reference COOPB20374”. JMG, JF and AL-G acknowledge support from the Spanish R&D Program through projects MULTI-SDM (CGL2015-66583-R) and INSIGNIA (CGL2016-79210-R), co-funded by the European Regional Development Fund (ERDF/FEDER). AL-G acknowledges support from the Spanish R&D Program through the predoctoral contract BES-2016-078158. 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. MB acknowledges support from the Simons Associateship of the Abdus Salam International Centre for Theoretical Physics. RH acknowledges support from the project LTT17007 funded by the Ministry of Education, Youth, and Sports of the Czech Republic.

Author information

Affiliations

  1. Department of Atmospheric and Ocean Sciences, Faculty of Exact and Natural Sciences, University of Buenos Aires (DCAO-FCEN-UBA), Buenos Aires, Argentina

    M. L. Bettolli, S. A. Solman, M. E. Olmo, R. Balmaceda Huarte & M. Doyle

  2. National Council of Scientific and Technical Research (CONICET), Buenos Aires, Argentina

    M. L. Bettolli, M. E. Olmo & R. Balmaceda Huarte

  3. Institut Franco‐Argentin d’Estudes sur le Climat et ses Impacts, Unité Mixte Internationale (UMI-IFAECI/CNRS-CONICET-UBA), Buenos Aires, Argentina

    M. L. Bettolli, S. A. Solman, M. E. Olmo, R. Balmaceda Huarte, J. Blázquez, M. Doyle & M. Feijoó

  4. Centro de Investigaciones del Mar y La Atmósfera (CIMA), CONICET-UBA, Buenos Aires, Argentina

    S. A. Solman, J. Blázquez, M. Doyle & M. Feijoó

  5. Departamento de Ciências Atmosféricas, Universidade de São Paulo (USP), São Paulo, SP, Brazil

    R. P. da Rocha

  6. Universidade Estadual Paulista Júlio de Mesquita Filho (UNESP), Bauru, SP, Brazil

    M. Llopart

  7. Meteorology Group, Instituto de Física de Cantabria (IFCA), CSIC-Univ. Cantabria, Santander, Spain

    J. M. Gutierrez & A. Lavin-Gullon

  8. Meteorology Group, Department of Applied Mathematics and Computer Science, Universidad de Cantabria, Santander, Spain

    J. Fernández

  9. Centro de Previsão de Tempo e Estudos Climáticos-INPE, São Paulo, SP, Brazil

    S. C. Chou

  10. Instituto Nacional de Pesquisas Espaciais (INPE), São José dos Campos, SP, Brazil

    D. Carneiro Rodrigues & L. Machado

  11. International Centre for Theoretical Physics (International Center for Theoretical Physics (ICTP)), Trieste, Italy

    E. Coppola

  12. Departamento de Ciencias de la Atmósfera, Facultad de Ciencias, Universidad de la República, Montevideo, Uruguay

    M. Barreiro

  13. Facultad de Ciencias Astronómicas y Geofísicas, Universidad Nacional de La Plata, La Plata, Argentina

    J. Blázquez

  14. Department of Climatology, Institute of Atmospheric Physics, Academy of Sciences of the Czech Republic, Prague, Czech Republic

    R. Huth

  15. Department of Physical Geography and Geoecology, Faculty of Science, Charles University, Prague, Czech Republic

    R. Huth

  16. Brazilian Agricultural Research Corporation (EMBRAPA), Brasília, DF, Brazil

    S. Vianna Cuadra

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  1. M. L. Bettolli
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  2. S. A. Solman
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  3. R. P. da Rocha
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  4. M. Llopart
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  5. J. M. Gutierrez
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  7. M. E. Olmo
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  9. S. C. Chou
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  10. D. Carneiro Rodrigues
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  11. E. Coppola
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  12. R. Balmaceda Huarte
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  13. M. Barreiro
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  14. J. Blázquez
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Correspondence to M. L. Bettolli.

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Bettolli, M.L., Solman, S.A., da Rocha, R.P. et al. The CORDEX Flagship Pilot Study in southeastern South America: a comparative study of statistical and dynamical downscaling models in simulating daily extreme precipitation events. Clim Dyn (2021). https://doi.org/10.1007/s00382-020-05549-z

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Keywords

  • Extreme precipitation
  • Statistical and dynamical downscaling
  • Observational uncertainty
  • Southeastern South America