Articles | Volume 14, issue 3
https://doi.org/10.5194/gmd-14-1595-2021
https://doi.org/10.5194/gmd-14-1595-2021
Development and technical paper
 | 
19 Mar 2021
Development and technical paper |  | 19 Mar 2021

CrocO_v1.0: a particle filter to assimilate snowpack observations in a spatialised framework

Bertrand Cluzet, Matthieu Lafaysse, Emmanuel Cosme, Clément Albergel, Louis-François Meunier, and Marie Dumont

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Latest update: 20 Jul 2024
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Short summary
In the mountains, the combination of large model error and observation sparseness is a challenge for data assimilation. Here, we develop two variants of the particle filter (PF) in order to propagate the information content of observations into unobserved areas. By adjusting observation errors or exploiting background correlation patterns, we demonstrate the potential for partial observations of snow depth and surface reflectance to improve model accuracy with the PF in an idealised setting.