Assessment of a multi-resolution snow reanalysis framework: a
multi-decadal reanalysis case over the Upper Yampa River Basin,
Colorado
Abstract. A multi-resolution (MR) approach was successfully implemented in the context of a data assimilation (DA) framework to efficiently estimate snow water equivalent (SWE) over a large headwater catchment in the Colorado River Basin (CRB), while decreasing computational constraints by 60 %. Thirty-one years of fractional snow cover area (fSCA) images derived from Landsat TM, ETM+ and OLI sensors measurements were assimilated to generate two SWE reanalysis datasets, a baseline case at a uniform 90 m spatial resolution and another using the MR approach. A comparison of the two showed negligible differences in terms of snow accumulation, melt and timing for the posterior estimates (in terms of both ensemble median and standard deviation). The MR approach underestimated the baseline peak SWE by less than 2 %, and day of peak and duration of the accumulation season by a day on average. The largest differences were, by construct, limited primarily to areas of low complexity, where shallow snowpacks tend to exist. The MR approach should allow for more computationally efficient implementations of snow data assimilation applications over large-scale mountain ranges with accuracies similar to those that would be obtained using ~ 100 m simulations. Such uniform resolution applications are generally infeasible due to the computationally expensive nature of ensemble-based DA frameworks.
