SNOWCOP: Advancing High-Resolution Retrospective SWE Reconstruction in the Andes of Chile and Argentina with Remote Sensing

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). 

 

References 

Cortés, G., & Margulis, S. (2017). Impacts of El Niño and La Niña on interannual snow accumulation in the Andes: Results from a high‐resolution 31 year reanalysis. Geophysical Research Letters, 44(13), 6859-6867. 

Liston, G. E., & Elder, K. (2006). A meteorological distribution system for high-resolution terrestrial modeling (MicroMet). Journal of Hydrometeorology, 7(2), 217-234. 

Marsh, C. B., Pomeroy, J. W., and Wheater, H. S.: The Canadian Hydrological Model (CHM) v1.0: a multi-scale, multi-extent, variable-complexity hydrological model – design and overview, Geosci. Model Dev., 13, 225–247. 

Pellicciotti, F., Brock, B., Strasser, U., Burlando, P., Funk, M., & Corripio, J. (2005). An enhanced temperature-index glacier melt model including the shortwave radiation balance: development and testing for Haut Glacier d’Arolla, Switzerland. Journal of glaciology, 51(175), 573-587. 

Premier, V., Marin, C., Steger, S., Notarnicola, C., & Bruzzone, L. (2021). A novel approach based on a hierarchical multiresolution analysis of optical time series to reconstruct the daily high-resolution snow cover area. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, 9223-9240.