Assessment of a multiresolution snow reanalysis framework: a multidecadal reanalysis case over the upper Yampa River basin, Colorado

Elisabeth Baldo,Steven A Margulis

doi:10.5194/hess-22-3575-2018

Elisabeth Baldo, Steven A Margulis

Open Access

https://doi.org/10.5194/hess-22-3575-2018

Copy DOI

Abstract

Abstract. A multiresolution (MR) approach was successfully implemented in the context of a data assimilation (DA) framework to efficiently estimate snow water equivalent (SWE) over a large head water catchment in the Colorado River basin (CRB), while decreasing computational constraints by 60 %. A total of 31 years of fractional snow cover area (fSCA) images derived from Landsat TM, ETM+, and OLI sensor 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 coefficient of variation). The MR approach underestimated the baseline peak SWE by less than 2 % and underestimated 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.

Highlights

Spatial resolutions of 100 m or less are more commonly being recommended when using land surface models (Wood et al, 2011; Bierkens et al, 2015; Beven et al, 2015), especially when trying to capture the heterogeneity of snowpack states in montane regions (Clark et al, 2011; Winstral et al, 2014)
This study demonstrated the performance of a new MR terrain discretization approach in the context of a snow reanalysis framework using the assimilation of Landsat-derived fractional snow cover area (fSCA) observations
The MR approach was shown to have an insignificant impact on the fSCA observations assimilated and the reanalysis framework led to posterior snow water equivalent (SWE) ensembles similar to the high-resolution 90 m baseline

Summary

Introduction

Spatial resolutions of 100 m or less are more commonly being recommended when using land surface models (Wood et al, 2011; Bierkens et al, 2015; Beven et al, 2015), especially when trying to capture the heterogeneity of snowpack states in montane regions (Clark et al, 2011; Winstral et al, 2014). Previous work using hydrologic response units (HRUs; Beven and Kirby, 1979; US Geological Survey et al, 1983; Sivapalan et al, 1987; Chaney et al, 2016), or triangulated irregular networks (TINs; Tucker et al, 2001; Vivoni et al, 2004; Mascaro et al, 2015) showed that simulating in a “one size fits all” (uniform grid) approach is computationally expensive, and suboptimal since only small subsets of watersheds require being resolved at fine spatial resolutions Along these lines, Baldo and Margulis (2017) developed a multiresolution (MR) scheme for raster-based models and tested it in the context of deterministic snow modeling.

Objectives

Methods

Findings

Conclusion