Abstract
SNOWCOP is a Horizon Europe project aimed at developing and evaluating a new high-resolution reanalysis dataset of snow water equivalent (SWE) and glacier ice melt rates for the extra-tropical Andes. The project integrates Copernicus and complementary remote sensing products within a physically based modeling framework to generate daily SWE and ice melt rate maps at 50 m spatial resolution, covering the period from 2002 to the present. These products address a critical observational gap in the region, where ground-based snow and meteorological measurements remain sparse. To support the development and validation of the SNOWCOP workflow, the initial phase of the project focuses on two pilot basins: the Río Maipo (Chile) and the Upper Río Mendoza (Argentina). These basins were selected due to their long term and high-quality instrumental SWE records, making good candidates for method’s evaluation.
We present the first results of a retrospective SWE reconstruction that integrates high-resolution daily snow cover maps with snowmelt modeling. The snow cover products are generated by applying a gap-filling and downscaling algorithm to coarse-resolution snow cover fraction data fused with high-resolution multi-source optical observations (Premier et al., 2021). Several snowmelt modeling approaches are evaluated, including a simple temperature-index (TI) model, an enhanced temperature-index (ETI) model (Pellicciotti et al., 2005), and fully physics-based formulations. Model coefficients are derived through calibration against in-situ observations. Meteorological forcings are obtained from ERA5 reanalysis data and dynamically downscaled using MicroMet (Liston & Elder, 2006). The reconstructed SWE is evaluated against ground-based measurements and compared with an existing SWE reanalysis dataset (Cortés & Margulis, 2017). as well as modeling results produced by our team (CHM model - Marsh et al., 2020).