Articles | Volume 15, issue 11
https://doi.org/10.5194/tc-15-5017-2021
https://doi.org/10.5194/tc-15-5017-2021
Research article
 | 
01 Nov 2021
Research article |  | 01 Nov 2021

Assimilating near-real-time mass balance stake readings into a model ensemble using a particle filter

Johannes Marian Landmann, Hans Rudolf Künsch, Matthias Huss, Christophe Ogier, Markus Kalisch, and Daniel Farinotti

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Cited articles

Arulampalam, M. S., Maskell, S., Gordon, N., and Clapp, T.: A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking, IEEE T. Signal Proces., 50, 174–188, https://doi.org/10.1109/78.978374, 2002. a
Barry, R.: Mountain Weather and Climate, Physical Environment Series, Routledge, 1992. a
Bauder, A., Funk, M., and Huss, M.: Ice-volume changes of selected glaciers in the Swiss Alps since the end of the 19th century, Ann. Glaciol., 46, 145–149, https://doi.org/10.3189/172756407782871701, 2007. a
Beniston, M., Farinotti, D., Stoffel, M., Andreassen, L. M., Coppola, E., Eckert, N., Fantini, A., Giacona, F., Hauck, C., Huss, M., Huwald, H., Lehning, M., López-Moreno, J.-I., Magnusson, J., Marty, C., Morán-Tejéda, E., Morin, S., Naaim, M., Provenzale, A., Rabatel, A., Six, D., Stötter, J., Strasser, U., Terzago, S., and Vincent, C.: The European mountain cryosphere: a review of its current state, trends, and future challenges, The Cryosphere, 12, 759–794, https://doi.org/10.5194/tc-12-759-2018, 2018. a
Bernardo, J. M. and Smith, A. F.: Bayesian theory, vol. 405, John Wiley & Sons, Hoboken, New Jersey, USA, 2009. a
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Short summary
In this study, we (1) acquire real-time information on point glacier mass balance with autonomous real-time cameras and (2) assimilate these observations into a mass balance model ensemble driven by meteorological input. For doing so, we use a customized particle filter that we designed for the specific purposes of our study. We find melt rates of up to 0.12 m water equivalent per day and show that our assimilation method has a higher performance than reference mass balance models.