Articles | Volume 22, issue 7
https://doi.org/10.5194/hess-22-3575-2018
https://doi.org/10.5194/hess-22-3575-2018
Research article
 | 
02 Jul 2018
Research article |  | 02 Jul 2018

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

Elisabeth Baldo and Steven A. Margulis

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Cited articles

Andreadis, K. M. and Lettenmaier, D. P.: Assimilating remotely sensed snow observations into a macroscale hydrology model, Adv. Water Resour., 29, 872–886, https://doi.org/10.1016/j.advwatres.2005.08.004, 2006. a
Arsenault, K. R., Houser, P. R., De Lannoy, G. J. M., and Dirmeyer, P. A.: Impacts of snow cover fraction data assimilation on modeled energy and moisture budgets, J. Geophys. Res.-Atmos., 118, 7489–7504, https://doi.org/10.1002/jgrd.50542, 2013. a
Baldo, E. and Margulis, S. A.: Implementation of a physiographic complexity-based multiresolution snow modeling scheme, Water Resour. Res., 53, 3680–3694, https://doi.org/10.1002/2016WR020021, 2017. a, b, c, d, e, f, g, h, i, j, k, l, m
Beven, K. J., Cloke, H., Pappenberger, F., Lamb, R., and Hunter, N.: Hyperresolution information and hyperresolution ignorance in modelling the hydrology of the land surface, Sci. China Earth Sci., 58, 25–35, https://doi.org/10.1007/s11430-014-5003-4, 2015. a
Beven, K. J. and Kirby, M. J.: A physically based, variable contributing area model of basin hydrology, Hydrolog. Sci. Bull., 24, 43–69, https://doi.org/10.1080/02626667909491834, 1979. a
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Short summary
Montane snowpacks are extremely complex to represent and usually require assimilating remote sensing images at very fine spatial resolutions, which is computationally expensive. Adapting the grid size of the terrain to its complexity was shown to cut runtime and storage needs by half while preserving the accuracy of ~ 100 m snow estimates. This novel approach will facilitate the large-scale implementation of high-resolution remote sensing data assimilation over snow-dominated montane ranges.