Abstract. Knowledge of current snow cover extent is essential for characterizing energy and moisture fluxes at the Earth's surface. The snow-covered area (SCA) is often estimated by using optical satellite information in combination with the normalized-difference snow index (NDSI). The NDSI thereby uses a threshold for the definition if a satellite pixel is assumed to be snow covered or snow free. The spatiotemporal representativeness of the standard threshold of 0.4 is however questionable at the local scale. Here, we use local snow cover maps derived from ground-based photography to continuously calibrate the NDSI threshold values (NDSI thr ) of Landsat satellite images at two European mountain sites of the period from 2010 to 2015. The Research Catchment Zugspitzplatt (RCZ, Germany) and Vernagtferner area (VF, Austria) are both located within a single Landsat scene. Nevertheless, the long-term analysis of the NDSI thr demonstrated that the NDSI thr at these sites are not correlated (r = 0.17) and different than the standard threshold of 0.4. For further comparison, a dynamic and locally optimized NDSI threshold was used as well as another locally optimized literature threshold value (0.7). It was shown that large uncertainties in the prediction of the SCA of up to 24.1 % exist in satellite snow cover maps in cases where the standard threshold of 0.4 is used, but a newly developed calibrated quadratic polynomial model which accounts for seasonal threshold dynamics can reduce this error. The model minimizes the SCA uncertainties at the calibration site VF by 50 % in the evaluation period and was also able to improve the results at RCZ in a significant way. Additionally, a scaling experiment shows that the positive effect of a locally adapted threshold diminishes using a pixel size of 500 m or larger, underlining the general applicability of the standard threshold at larger scales.

In order to investigate the effect of changing precipitation type on glacier discharge due to air-temperature changes, the relation between summer snowfall and runoff is surveyed for the Vernagtbach basin, Austria, (2640–3630ma.s.l.; ~72% glaciated) for the period 1976–2005. Precipitation data were evaluated for each ablation season with respect to amount and type; the latter derived mainly from daily photographs of the catchment, but validated over 4 years with additional meteorological data. Winter snowfall amounts were determined on the basis of mass-balance measurements. Average ablation period air temperature showed a rise of 1.5 K from 1976 to 2005, and runoff increased from about 1100 mmw.e. to 2200 mmw.e. Snowfall amounts during the ablation period decreased between 1976 and 1991, but increased from 1992 to 2005, indicating a large year-to-year variation. The number of days with snowfall varies even more, with no clear trend discernible. The evolution of runoff is only partly explained by precipitation type during the ablation season, and accumulation amounts during winter deliver a not unambiguous picture. More important is the development of the ablation area from about 20% of glacier size in the 1970s to 100% in 2003.

Abstract. Knowledge about the current snow cover extent is essential for characterising energy and moisture fluxes at the earth surface. The snow-covered area (SCA) is often estimated by using optical satellite information in combination with the normalized-difference snow index (NDSI) .The NDSI thereby uses a threshold for the definition if a satellite pixel is assumed to be snow covered or snow free. The spatio-temporal representativeness of the standard threshold of 0.4 is however questionable at the local scale. Here, we use local snow cover maps derived from ground-based photography to continuously 15 calibrate the NDSI threshold values ( ℎ ) of Landsat satellite images at two European mountain sites of the period from 2010 to 2015. Both sites, the Research Catchment Zugspitzplatt (RCZ, Germany) and the Vernagtferner area (VF, Austria), are located within a single Landsat scene. Nevertheless, the long-term analysis of the ℎ demonstrated that the ℎ at these sites are not correlated and different to the standard threshold of 0.4. For further comparison, a dynamic and locally optimized NDSI threshold was used as well as another literature threshold value. It was shown that large uncertainties in the 20 prediction of the SCA of up to 24.1% exist in satellite snow cover maps in case the standard threshold of 0.4 is used, but a newly developed calibrated quadratic polynomial model which is accounting for seasonal threshold dynamics can reduce this error. The model minimizes the SCA uncertainties at the calibration site VF by 50% in the evaluation period and was also able to improve the results at RCZ in a significant way. Additionally, a scaling experiment has shown that the positive effect of a locally adapted threshold diminishes from a pixel size of 500m and more which underlines the general applicability of the 25 standard threshold at larger scales.

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