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Sensitivity of snow models to the accuracy of meteorological forcings in mountain environments

Academic Article
Publication Date:
2020
abstract:
Snow models are usually evaluated at sites providing high-quality meteorological data, so that the uncertainty in the meteorological input data can be neglected when assessing model performances. However, high-quality input data are rarely available in mountain areas and, in practical applications, the meteorological forcing used to drive snow models is typically derived from spatial interpolation of the available in situ data or from reanalyses, whose accuracy can be considerably lower. In order to fully characterize the performances of a snow model, the model sensitivity to errors in the input data should be quantified.
Iris type:
01.01 Articolo in rivista
Keywords:
snow models; alps; model sensitivity; sensitivity experiment
List of contributors:
GRAF VON HARDENBERG, JOST DIEDRICH; Palazzi, Elisa; Provenzale, Antonello; Terzago, Silvia
Authors of the University:
PROVENZALE ANTONELLO
TERZAGO SILVIA
Handle:
https://iris.cnr.it/handle/20.500.14243/382969
Published in:
HYDROLOGY AND EARTH SYSTEM SCIENCES
Journal
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