Articles | Volume 26, issue 12
Hydrol. Earth Syst. Sci., 26, 3037–3054, 2022
https://doi.org/10.5194/hess-26-3037-2022
Hydrol. Earth Syst. Sci., 26, 3037–3054, 2022
https://doi.org/10.5194/hess-26-3037-2022
Research article
21 Jun 2022
Research article | 21 Jun 2022

Bias adjustment and downscaling of snow cover fraction projections from regional climate models using remote sensing for the European Alps

Michael Matiu and Florian Hanzer

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Cited articles

Brun, E., Martin, E., Simon, V., Gendre, C., and Coleou, C.: An Energy and Mass Model of Snow Cover Suitable for Operational Avalanche Forecasting, J. Glaciol., 35, 333–342, https://doi.org/10.3189/S0022143000009254, 1989. 
Cannon, A. J.: Multivariate quantile mapping bias correction: an N-dimensional probability density function transform for climate model simulations of multiple variables, Clim. Dynam., 50, 31–49, https://doi.org/10.1007/s00382-017-3580-6, 2018. 
Cannon, A. J., Sobie, S. R., and Murdock, T. Q.: Bias Correction of GCM Precipitation by Quantile Mapping: How Well Do Methods Preserve Changes in Quantiles and Extremes?, J. Climate, 28, 6938–6959, https://doi.org/10.1175/JCLI-D-14-00754.1, 2015. 
CH2018: CH2018 – Climate Scenarios for Switzerland, Technical Report, National Centre for Climate Services, Zurich, ISBN 978-3-9525031-4-0, 2018. 
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Short summary
Regional climate models not only provide projections on temperature and precipitation, but also on snow. Here, we employed statistical post-processing using satellite observations to reduce bias and uncertainty from model projections of future snow-covered area and duration under different greenhouse gas concentration scenarios for the European Alps. Snow cover area/duration decreased overall in the future, three times more strongly with 4–5° global warming as compared to 1.5–2°.