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Bias correction of global irradiance modelled with the Weather Research and Forecasting model over Paraguay

dc.contributor.authorGonzalez Cuevas, Juan Alberto 
dc.contributor.authorRincón Rodriguez, Angel 
dc.contributor.authorJorba, Oriol
dc.contributor.authorFrutos, Miguel
dc.contributor.authorAlvarez, Leopoldo
dc.contributor.authorBarrios, Fernando
dc.contributor.otherUniversidad Nacional de Asunción - Facultad de Ingenieríaes
dc.contributor.otherBarcelona Supercomputing Center (BSC-CNS) (ES)es
dc.contributor.otherHarmattan Solutions (ES)es
dc.date.accessioned2022-04-23T21:34:36Z
dc.date.available2022-04-23T21:34:36Z
dc.date.issued2016
dc.identifier.urihttp://hdl.handle.net/20.500.14066/3197
dc.description.abstract" In this contribution, we present a post-process analysis of the Weather Research and Forecasting (WRF) model which combines a Kalman Filter with Model Output Statistics for bias correction in order to improve the overall predicted values of GHI simulations over Paraguay. The hourly GHI is simulated at 4x4 km2 of spatial resolution. The annual evaluation of the hourly WRF model without post process shows relative mean bias error (rMBE) of 21% and relative root mean square error (rRMSE) of 81%. The results using several ground stations and combinations of post-process show an annual correction of systematic errors with rMBE of -0.7% and rRMSE of 70%."es
dc.description.sponsorshipCONACYT - Consejo Nacional de Ciencias y Tecnologíaes
dc.language.isoenges
dc.subject.classification1 Exploración y explotación de la tierraes
dc.subject.otherSOLAR IRRADIANCEes
dc.subject.otherNUMERICAL WEATHER PREDICTIONes
dc.subject.otherSTATISTICAL POST-PROCESSes
dc.subject.otherKALMAN FILTERes
dc.subject.otherMODEL OUTPUT STATISTICSes
dc.subject.otherFISICA NUCLEARes
dc.subject.otherBIOFISICA MOLECULARes
dc.titleBias correction of global irradiance modelled with the Weather Research and Forecasting model over Paraguayes
dc.typeresearch articlees
dc.conference.date2016-10
dc.conference.placePalma de Mallorca, ESes
dc.conference.titleEuroSun 2016es
dc.description.fundingtextPROCIENCIAes
dc.relation.projectCONACYT14-INV-289es
dc.rights.accessRightsopen accesses


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