Abstract
AbstractPrecipitation downscaling in mountainous regions with sparse station data is challenging, but needed to link global climate datasets with high-resolution glacier models. In this study, we apply a linear orographic precipitation model (OPM) to generate orographic precipitation fields for mass-balance studies at Gran Campo Nevado (GCN), Southern Patagonia. The OPM is driven by large-scale atmospheric input variables taken from the reanalysis data of the US National Centers for Environmental Prediction and the US National Center for Atmospheric Research. The orographic precipitation fields are compared to precipitation fields assessed by a linear precipitation gradient, widely used in earlier mass-balance studies of GCN and elsewhere. Both downscaling methods are implemented into a degree-day model to analyze the sensitivity of mass-balance modeling to different precipitation inputs. Significant spatio-temporal differences are found, particularly in the summit region. The mass-balance modeling shows high sensitivity to the different precipitation distribution methods, leading to differences in the mass-balance gradients on the east side of GCN.
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