Preprints
https://doi.org/10.5194/hess-2021-449
https://doi.org/10.5194/hess-2021-449

  23 Sep 2021

23 Sep 2021

Review status: this preprint is currently under review for the journal HESS.

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

Michael Matiu1 and Florian Hanzer2 Michael Matiu and Florian Hanzer
  • 1Institute for Earth Observation, Eurac Research, Bolzano, 39100, Italy
  • 2Department of Geography, University of Innsbruck, Innsbruck, 6020, Austria

Abstract. Mountain seasonal snow cover is undergoing major changes due to global climate change. Assessments of future snow cover usually rely on physical based models, and often include post-processed meteorology. Alternatively, here we propose a direct statistical adjustment of snow cover fraction from regional climate models by using long-term remote sensing observations. We compared different bias correction routines (delta change, quantile mapping, and quantile delta mapping) and explore a downscaling based on historical observations for the Greater Alpine Region in Europe. All bias correction methods adjust for systematic biases, for example due to topographic smoothing, and reduce model spread in future projections. Averaged over the study region and whole year, snow cover fraction decreases from 12.5 % in 2000–2020 to 10.4 (8.9, 11.5; model spread) % in 2071–2100 under RCP2.6, and 6.4 (4.1, 7.8) % under RCP8.5. In addition, changes strongly depended on season and altitude. The comparison of the statistical downscaling to a high-resolution physical based model yields similar results for the altitude range covered by the climate models, but different altitudinal gradients of change above and below. We found trend-preserving bias correction methods (delta change, quantile delta mapping) more plausible for snow cover fraction than quantile mapping. Downscaling showed potential but requires further research. Since climate model and remote sensing observations are available globally, the proposed methods are potentially widely applicable, but are limited to snow cover fraction only.

Michael Matiu and Florian Hanzer

Status: open (until 18 Nov 2021)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Michael Matiu and Florian Hanzer

Data sets

Bias corrected and downscaled snow cover fraction from EURO-CORDEX RCMs for the Greater Alpine Region Michael Matiu https://doi.org/10.5281/zenodo.5266359

Michael Matiu and Florian Hanzer

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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.