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dc.contributor.authorCUADRA, S. V.
dc.contributor.authorOLIVEIRA, M. P. G. de
dc.contributor.authorVICTORIA, D. de C.
dc.contributor.authorBENDER, F. D.
dc.contributor.authorBETTOLLI, M. L.
dc.contributor.authorSOLMAN, S.
dc.contributor.authorROCHA, R. P. da
dc.contributor.authorFERNÁNDEZ, J.
dc.contributor.authorMILOVAC, J.
dc.contributor.authorCOPOLLA, E.
dc.contributor.authorDOYLE, M.
dc.date.accessioned2025-04-22T16:47:31Z-
dc.date.available2025-04-22T16:47:31Z-
dc.date.created2025-04-07
dc.date.issued2025
dc.identifier.citationAgriEngineering, v. 7, n. 4, 108, 2025.
dc.identifier.issn2624-7402
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1174595-
dc.descriptionAbstract: 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. Inter-institutional collaboration and coordinated science are key aspects to address these end-to-end studies in South America, since there is no single institution able to produce such CPRCM-CropModels ensembles.
dc.language.isoeng
dc.rightsopenAccess
dc.subjectRegional climate model
dc.subjectConvection permitting
dc.subjectCrop growth model
dc.subjectMaize
dc.titleApplication of high-resolution regional climate model simulations for crop yield estimation in Southern Brazil.
dc.typeArtigo de periódico
dc.subject.thesagroModelo de Simulação
dc.subject.thesagroClima
dc.subject.thesagroRendimento
dc.subject.thesagroMilho
dc.subject.thesagroSoja
dc.subject.thesagroProdutividade
dc.subject.nalthesaurusClimate models
dc.subject.nalthesaurusCrop models
dc.subject.nalthesaurusGrowth models
dc.subject.nalthesaurusCorn
dc.subject.nalthesaurusSoybeans
riaa.ainfo.id1174595
riaa.ainfo.lastupdate2025-04-22
dc.identifier.doihttps://doi.org/10.3390/agriengineering7040108
dc.contributor.institutionSANTIAGO VIANNA CUADRA, CNPTIA; MONIQUE PIRES GRAVINA DE OLIVEIRA; DANIEL DE CASTRO VICTORIA, CNPTIA; FABIANE DENISE BENDER; MARIA L BETTOLLI, UNIVERSIDAD DE BUENOS AIRES; SILVINA SOLMAN, UNIVERSIDAD DE BUENOS AIRES; ROSMERI PORFÍRIO DA ROCHA, UNIVERSIDADE DE SÃO PAULO; JESÚS FERNÁNDEZ, UNIVERSIDADE DE CANTABRIA; JOSIPA MILOVAC, UNIVERSIDAD DE CANTABRIA; ERIKA COPOLLA, INTERNATIONAL CENTRE FOR THEORETICAL PHYSICS; MOIRA DOYLE, NATIONAL UNIVERSITY OF LA PLATA.
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