Gold Standard in selection of rainfall forecasting models for soybean crops region

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dc.catalogadoryvc
dc.contributor.authorOliveira, Marcio Paulo de
dc.contributor.authorUribe-Opazo, Miguel Ángel
dc.contributor.authorGalea Rojas, Manuel Jesús
dc.contributor.authorJohann, Jerry Adriani
dc.date.accessioned2024-04-16T19:47:34Z
dc.date.available2024-04-16T19:47:34Z
dc.date.issued2022
dc.description.abstractRainfall data forecasting is essential in agricultural sciences due to impacts caused by water excess or deficit on crop growth. Our study aimed to develop a method to select rainfall forecast models using references with negligible error denoted as the gold standard. To this end, we used forecasting models from national centers such as Canadian Meteorological Center (CMC), European Center for Medium-Range Weather Forecasts (ECMWF), National Center for Environmental Prediction (NCEP), and Center for Weather Forecasting and Climate Studies (CPTEC). The study area comprised the western mesoregion of Paraná State (Brazil), and data were gathered from October to March between the soybean crop seasons of 2010/2011 and 2015/2016. Ten-day period clusters, corresponding to 240 h forecasts in the centers, were used to assess agreement with the gold standard. Our results showed that forecasting center selection must be based on rainfall value ranges and geographic locations. Selection according to the highest agreement with the gold standard was estimated at 76.9% for range 1 in CPTEC, 38.5% for range 2 and 4 in ECMWF, and 38.5% for range 3 in NCEP. In conclusion, the proposed method was efficient in selecting forecasting centers in areas of interest.
dc.description.funderCoordination for the Improvement of Higher Level Personnel ?
dc.description.funderPGEAGRI
dc.description.funderCAPES
dc.description.funderFONDECYT
dc.description.funderCNPq
dc.description.funderUNIOESTE
dc.description.funderUTFPR
dc.fechaingreso.objetodigital2024-04-16
dc.fuente.origenScopus
dc.identifier.doi10.21475/ajcs.22.16.04.p3449
dc.identifier.eissn18352707
dc.identifier.issn18352693
dc.identifier.scopusidSCOPUS_ID:85132534370
dc.identifier.urihttps://doi.org/10.21475/ajcs.22.16.04.p3449
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/85143
dc.information.autorucFacultad de Matemáticas; Galea Rojas, Manuel Jesús; 0000-0001-9819-5843 ; 1008589
dc.issue.numero4
dc.language.isoen
dc.nota.accesocontenido completo
dc.pagina.final500
dc.pagina.inicio495
dc.publisherSouthern Cross Publishing
dc.revistaAustralian Journal of Crop Science
dc.rightsacceso abierto
dc.rights.licenseCC BY-NC 4.0 DEED Attribution-NonCommercial 4.0 International
dc.rights.urihttps://www.creativecommons.org/licenses/by-nc/4.0/deed.en
dc.subjectAgreement
dc.subjectModel selection
dc.subjectRainfall forecast
dc.subjectSpatial variation
dc.subject.ddc600
dc.subject.deweyTecnologíaes_ES
dc.subject.ods13 Climate action
dc.subject.odspa13 Acción por el clima
dc.titleGold Standard in selection of rainfall forecasting models for soybean crops region
dc.typeartículo
dc.volumen16
sipa.codpersvinculados1008589
sipa.trazabilidadSCOPUS;2022-07-08
sipa.trazabilidadORCID;2024-04-15
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