@article{10902/36391,
year = {2025},
month = {4},
url = {https://hdl.handle.net/10902/36391},
abstract = {This study is focused on assessing the impacts of different regional climate model targeted simulations performed at convection-permitting resolution (CPRCM) in the AgS crop model yield simulations, evaluating to what extent climate model uncertainty impacts the modeled yield-considering the spatial and temporal variability of crop yield simulations over central-south Brazil. The ensemble of CPRCMs has been produced as part of a Flagship Pilot Study (FPS-SESA) framework, endorsed by the Coordinated Regional Climate Downscaling Experiment (CORDEX). The AgS simulated crop yield exhibited significant differences, in both space and time, among the simulations driven by the different CPRCMs as well as when compared with the simulations driven by observations. Rainfall showed the highest uncertainty in CPRCM simulations, particularly in its spatial variability, whereas modeled temperature and solar radiation were generally more accurate and exhibited smaller spatial and temporal differences. The results evidenced the need for multi-model simulations to account for different uncertainty, from different climate models and climate models parameterizations, in crop yield estimations. Interinstitutional collaboration and coordinated science are key aspects to address these endto-end studies in South America, since there is no single institution able to produce such CPRCM-CropModels ensembles.},
organization = {We gratefully acknowledge the financial support by the National Institute of Science and Technology in Low Carbon Emission Agriculture (INCT-ABC) sponsored by Brazil’s National Council for Scientific and Technological Development (CNPq, grant no. 406635/2022-6), the Foundation for Research Support of the State of Rio Grande do Sul (Fapergs, grant no. 22/2551-0000392-3). This work was also supported by University of Buenos Aires Grant UBACYT2023 20020220200028BA, CONICET Grant PIP2023, 11220220100209CO.},
publisher = {MDPI},
publisher = {AgriEngineering, 2025, 7(4), 108},
title = {Application of high-resolution regional climate model simulations for crop yield estimation in Southern Brazil},
author = {Cuadra, Santiago Vianna and De Oliveira, Monique Pires Gravina and De Castro Victoria, Daniel and Bender, Fabiani Denise and Bettolli, Maria Laura and Solman, Silvina and Da Rocha, Rosmeri Porfírio and Fernández Fernández, Jesús (matemático) and Milovac, Josipa and Coppola, Erika and Doyle, Moira},
}