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dc.contributor.authorCasado-Rubio, J. L.
dc.contributor.authorRevuelta, M. A.
dc.contributor.authorPostigo, M.
dc.contributor.authorMartínez-Marco, I.
dc.contributor.authorYagüe, C.
dc.date.accessioned2017-06-09T16:51:42Z
dc.date.available2017-06-09T16:51:42Z
dc.date.issued2017
dc.identifier.issn1558-8424
dc.identifier.otherams-75447.pdf
dc.identifier.urihttp://onlinelibrary.yabesh.ir/handle/yetl/4217784
dc.description.abstractmethod for Direct Normal Irradiance (DNI) forecasting for specific sites is proposed. It is based on the combination of a numerical weather prediction (NWP) model, which provides cloud information, with radiative transfer simulations fed with external aerosol forecasts. The NWP model used is the ECMWF Integrated Forecast System and the radiative transfer information has been obtained from libRadtran 1D. Two types of aerosol forecasts have been tested: the global Monitoring Atmospheric Composition and Climate (MACC) model, which predicts five major components of the aerosol, and the regional Dust REgional Atmospheric Model (BSC-DREAM8b) added to a fixed background calculated as the 20th percentile of the monthly mean of AERONET 2.0 observations from a different year. The methodology employed is valid for all meteorological situations, providing a stable and continuous DNI curve. The performance of the combined method has been evaluated against DNI observations and compared with the pure ECMWF forecasts at eight locations in the southern half of mainland Spain and the Canary Islands, which received high loadings of African dust for 2013 and 2014. Results for 1-day forecasts are presented. Although clouds play a major role, aerosols have a significant effect, but at shorter timescales. The combination of ECMWF and MACC forecasts gives the best global results, improving the DNI forecasts in events with high aerosol content. The regional BSC-DREAM8b model yields good results for some extremely high dust conditions, though more reliable predictions, valid for any aerosol conditions, are provided by the MACC model.
dc.publisherAmerican Meteorological Society
dc.titleA post-processing methodology for direct normal irradiance forecasting using cloud information and aerosol load forecasts
dc.typeJournal Paper
dc.journal.volume056
dc.journal.issue006
dc.journal.titleJournal of Applied Meteorology and Climatology
dc.identifier.doi10.1175/JAMC-D-16-0297.1
dc.journal.fristpage1595
dc.journal.lastpage1608
dc.treeJournal of Applied Meteorology and Climatology:;2017:;volume( 056 ):;issue: 006
dc.contenttypeFulltext


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