Articles | Volume 27, issue 24
https://doi.org/10.5194/hess-27-4637-2023
https://doi.org/10.5194/hess-27-4637-2023
Research article
 | 
22 Dec 2023
Research article |  | 22 Dec 2023

Spatio-temporal information propagation using sparse observations in hyper-resolution ensemble-based snow data assimilation

Esteban Alonso-González, Kristoffer Aalstad, Norbert Pirk, Marco Mazzolini, Désirée Treichler, Paul Leclercq, Sebastian Westermann, Juan Ignacio López-Moreno, and Simon Gascoin

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Short summary
Here we explore how to improve hyper-resolution (5 m) distributed snowpack simulations using sparse observations, which do not provide information from all the areas of the simulation domain. We propose a new way of propagating information throughout the simulations adapted to the hyper-resolution, which could also be used to improve simulations of other nature. The method has been implemented in an open-source data assimilation tool that is readily accessible to everyone.