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

dc.contributorUniversidad Nacional de Asunción - Facultad de Ingeniería
dc.contributorBarcelona Supercomputing Center (BSC-CNS) (ES)
dc.contributorHarmattan Solutions (ES)
dc.creatorGonzalez Cuevas, Juan Alberto
dc.creatorRincón Rodriguez, Angel
dc.creatorJorba, Oriol
dc.creatorFrutos, Miguel
dc.creatorAlvarez, Leopoldo
dc.creatorBarrios, Fernando
dc.date2022-04-23T21:34:36Z
dc.date2022-04-23T21:34:36Z
dc.date2016
dc.date.accessioned2023-09-25T13:30:25Z
dc.date.available2023-09-25T13:30:25Z
dc.identifierhttp://hdl.handle.net/20.500.14066/3197
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/8806740
dc.description" 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%."
dc.descriptionCONACYT - Consejo Nacional de Ciencias y Tecnología
dc.descriptionPROCIENCIA
dc.languageeng
dc.relation14-INV-289
dc.rightsopen access
dc.subject1 Exploración y explotación de la tierra
dc.subjectSOLAR IRRADIANCE
dc.subjectNUMERICAL WEATHER PREDICTION
dc.subjectSTATISTICAL POST-PROCESS
dc.subjectKALMAN FILTER
dc.subjectMODEL OUTPUT STATISTICS
dc.subjectFISICA NUCLEAR
dc.subjectBIOFISICA MOLECULAR
dc.titleBias correction of global irradiance modelled with the Weather Research and Forecasting model over Paraguay
dc.typeresearch article


Este ítem pertenece a la siguiente institución