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dc.contributor.authorLaiti L
dc.contributor.authorGiovannini L
dc.contributor.authorZardi D
dc.contributor.authorBelluardo G
dc.contributor.authorMoser D
dc.date.accessioned2018-11-12T11:36:58Z
dc.date.available2018-11-12T11:36:58Z
dc.date.issued2018
dc.identifier.issn2073-4433
dc.identifier.urihttp://dx.doi.org/10.3390/atmos9040117
dc.identifier.urihttps://www.mdpi.com/2073-4433/9/4/117
dc.identifier.urihttp://hdl.handle.net/10863/7130
dc.description.abstractAccurate solar radiation estimates in Alpine areas represent a challenging task, because of the strong variability arising from orographic effects and mountain weather phenomena. These factors, together with the scarcity of observations in elevated areas, often cause large modelling uncertainties. In the present paper, estimates of hourly mean diffuse fraction values from global radiation data, provided by a number (13) of decomposition models (chosen among the most widely tested in the literature), are evaluated and compared with observations collected near the city of Bolzano, in the Adige Valley (Italian Alps). In addition, the physical factors influencing diffuse fraction values in such a complex orographic context are explored. The average accuracy of the models were found to be around 27% and 14% for diffuse and beam radiation respectively, the largest errors being observed under clear sky and partly cloudy conditions, respectively. The best performances were provided by the more complex models, i.e., those including a predictor specifically explaining the radiation components’ variability associated with scattered clouds. Yet, these models return non-negligible biases. In contrast, the local calibration of a single-equation logistical model with five predictors allows perfectly unbiased estimates, as accurate as those of the best-performing models (20% and 12% for diffuse and beam radiation, respectively), but at much smaller computational costsen_US
dc.language.isoenen_US
dc.rights
dc.titleEstimating Hourly Beam and Diffuse Solar Radiation in an Alpine Valley: A Critical Assessment of Decomposition Modelsen_US
dc.typeArticleen_US
dc.date.updated2018-11-12T10:42:12Z
dc.language.isiEN-GB
dc.journal.titleAtmosphere
dc.description.fulltextnoneen_US


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