A   reanalysis   of   one   decade   of   the   mass   balance   series   on 
Hintereisferner,  Ötztal  Alps,  Austria:  a  detailed  view  into  annual 
geodetic and glaciological observations

Klug, Christoph; Bollmann, E.; Galos, Stephan Peter; Nicholson, Lindsey; Prinz, Rainer; Rieg, Lorenzo; Sailer, Rudolf; Stötter, Johann; Kaser, Georg

doi:10.5194/tc-2017-132

Cited by 5 publications

(6 citation statements)

References 18 publications

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“…The average value of the ELA 0 (balanced-budget ELA) is found between 3050 m and 3150 m a.s.l. [34]. At this elevation range, the mean annual air temperature is around −5 • C and the annual precipitation (solid and liquid) about 1500 mm [34].…”

Section: Study Regionmentioning

confidence: 87%

“…[34]. At this elevation range, the mean annual air temperature is around −5 • C and the annual precipitation (solid and liquid) about 1500 mm [34]. The ablation period usually lasts from May to September.…”

Section: Study Regionmentioning

confidence: 91%

“…13) with 3.6 km 2 . Of these, Hintereisferner (HEF), Kesselwandferner (KWF), and Vernagtferner (VNF), have long and continuous time series of mass balance measurements, ELAs and AARs [18,[34][35][36][37], providing a valuable dataset for comparison with the automatically generated SLA and SCR estimates. The highest glacier elevation is reached at Taschachferner (3745 m a.s.l.)…”

Section: Study Regionmentioning

confidence: 99%

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On the Automated Mapping of Snow Cover on Glaciers and Calculation of Snow Line Altitudes from Multi-Temporal Landsat Data

et al. 2019

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Mapping snow cover (SC) on glaciers at the end of the ablation period provides a possibility to rapidly obtain a proxy for their equilibrium line altitude (ELA) which in turn is a metric for the mass balance. Satellite determination of glacier snow cover, derived over large regions, can reveal its spatial variability and temporal trends. Accordingly, snow mapping on glaciers has been widely applied using several satellite sensors. However, as glacier ice originates from compressed snow, both have very similar spectral properties and standard methods to map snow struggle to distinguish snow on glaciers. Hence, most studies applied manual delineation of snow extent on glaciers. Here we present an automated tool, named ‘ASMAG’ (automated snow mapping on glaciers), to map SC on glaciers and derive the related snow line altitude (SLA) for individual glaciers using multi-temporal Landsat satellite imagery and a digital elevation model (DEM). The method has been developed using the example of the Ötztal Alps, where an evaluation of the method is possible using field-based observations of the annual equilibrium line altitude (ELA) and the accumulation area ratio (AAR) measured for three glaciers for more than 30 years. The tool automatically selects a threshold to map snow on glaciers and robustly calculates the SLA based on the frequency distribution of elevation bins with more than 50% SC. The accuracy of the SC mapping was about 90% and the SLA was determined successfully in 80% of all cases with a mean uncertainty of ±19 m. When cloud-free scenes close to the date of the highest snowline are available, a good to very good agreement of SC ratios (SCR)/SLA with field data of AAR/ELA are obtained, otherwise values are systematically higher/lower as useful images were often acquired too early in the summer season. However, glacier specific differences are still well captured. Snow mapping on glaciers is impeded by clouds and their shadows or when fresh snow is covering the glaciers, so that more frequent image acquisitions (as now provided by Sentinel-2) would improve results.

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Section: Study Regionmentioning

confidence: 87%

Section: Study Regionmentioning

confidence: 91%

Section: Study Regionmentioning

confidence: 99%

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On the Automated Mapping of Snow Cover on Glaciers and Calculation of Snow Line Altitudes from Multi-Temporal Landsat Data

et al. 2019

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“…In these higher regions, seasonal snow cover lasts from October until the end of June. The geological bedrock in the Rofental area mainly consists of biotite-plagioclase, biotite and muscovite gneisses, variable mica schists, and gneissic schists of the Austroalpine Ötztal nappe (Kreuss, 2012;Moser, 2012). Subordinate lithologies are quartzites and graphite schists.…”

Section: The Rofental -Site Descriptionmentioning

confidence: 99%

The Rofental: a high Alpine research basin (1890–3770 m a.s.l.) in the Ötztal Alps (Austria) with over 150 years of hydrometeorological and glaciological observations

Strasser

Marke

Braun

et al. 2018

Earth Syst. Sci. Data

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Abstract. A comprehensive hydrometeorological and glaciological data set is presented, originating from a multitude of glaciological, meteorological, hydrological and laser scanning recordings at research sites in the Rofental (1891–3772 m a.s.l., Ötztal Alps, Austria). The data sets span a period of 150 years and hence represent a unique time series of rich high-altitude mountain observations. Their collection was originally initiated to support scientific investigation of the glaciers Hintereisferner, Kesselwandferner and Vernagtferner. Annual mass balance, glacier front variation, flow velocities and photographic records of the status of these glaciers were recorded. Later, additional measurements of meteorological and hydrological variables were undertaken, and over time a number of autonomous weather stations and runoff gauges were brought into operation; the available data now comprise records of temperature, relative humidity, short- and longwave radiation, wind speed and direction, air pressure, precipitation, and river water levels. Since 2001, a series of distributed (airborne and terrestrial) laser scans is available, along with associated digital surface models. In 2016 a permanent terrestrial laser scanner was installed on Im hintern Eis (3244 m a.s.l.) to continuously observe almost the entire area of Hintereisferner. The data and research undertaken at the sites of investigation in the Rofental area enable combined research of cryospheric, atmospheric and hydrological processes in complex terrain, and support the development of several state-of-the-art glacier mass balance and hydroclimatological models. The institutions taking part in the Rofental research framework promote their site in several international research initiatives. In INARCH (International Network for Alpine Research Catchment Hydrology, http://words.usask.ca/inarch), all original research data sets are now provided to the scientific community according to the Creative Commons Attribution License by means of the PANGAEA repository (https://doi.org/10.1594/PANGAEA.876120).

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“…For both these glaciers (i) topographic data is available in the form of high-resolution digital elevation models (DEMs) derived from airborne laser-scanning data acquired in Fall 2013 (Galos et al, 2015); (ii) meteorological data are available from automatic weather stations (AWSs) in the vicinity of the glaciers for the period 2012 to 2014 and (iii) intense glaciological observations, including measurements of seasonal mass balance (e.g. Klug et al, 2017;Galos et al, 2017), are available.…”

Section: Study Sites and Model Input Datamentioning

confidence: 99%

Robust uncertainty assessment of the spatio-temporal transferability of glacier mass and energy balance models

Zolles¹,

Maussion²,

Galos³

et al. 2018

Preprint

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Abstract. Energy and mass balance modeling of glaciers is a key tool for climate impact studies of future glacier behaviour. By incorporating many of the physical processes responsible for surface accumulation and ablation, they offer more insight than simpler statistical models and are believed to suffer less from problems of stationarity when applied under changing climate conditions. However, this view is challenged by the widespread use of parameterizations for some physical processes introduces a statistical calibration step. We argue that the reported uncertainty in modelled mass balance (and associated energy flux components) are likely to be understated in modelling studies that do not use spatio-temporal cross-validation and use a single performance measure for model optimization. To demonstrate the importance of these principles, we present a rigorous sensitivity and uncertainty assessment workflow applied to a modelling study of two glaciers in the European Alps. The procedure begins with a reduction of the model parameter space using a global sensitivity assessment that identifies the parameters to which the model responds most sensitively. We find that the model sensitivity to individual parameters varies considerably in space and time, indicating that a single stated model sensitivity value is unlikely to be realistic. The model is most sensitive to parameters related to snow albedo and vertical gradients of the meteorological forcing data. We then apply a Monte Carlo multi-objective optimization based on three performance measures: Model bias and mean absolute deviation in the upper and lower glacier parts, with glaciological mass balance data measured at individual stake locations used as reference. This procedure generates an ensemble of optimal parameter solutions which are equally valid. The range of parameters associated with these ensemble members are used to estimate the cross-validated uncertainty of the model output and computed energy components. The parameter values for the optimal solutions vary widely, and considering longer calibration periods does not systematically result in more constrained parameter choices. The resulting mass balance uncertainties reach up to 1300 kgm−2, with the spatial and temporal transfer errors having the same order of magnitude. The uncertainty of surface energy flux components over the ensemble at the point scale reached up to 50 % of the computed flux. The largest absolute uncertainties originate from the short-wave radiation and the albedo parametrizations, followed by the turbulent fluxes. Our study highlights the need for due caution, and realistic error quantification when applying such models to regional glacier modelling efforts, or for projections of glacier mass balance in climate settings that are substantially different from the conditions in which the model was optimized.

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A reanalysis of one decade of the mass balance series on Hintereisferner, Ötztal Alps, Austria: a detailed view into annual geodetic and glaciological observations

Cited by 5 publications

References 18 publications

On the Automated Mapping of Snow Cover on Glaciers and Calculation of Snow Line Altitudes from Multi-Temporal Landsat Data

On the Automated Mapping of Snow Cover on Glaciers and Calculation of Snow Line Altitudes from Multi-Temporal Landsat Data

The Rofental: a high Alpine research basin (1890–3770 m a.s.l.) in the Ötztal Alps (Austria) with over 150 years of hydrometeorological and glaciological observations

Robust uncertainty assessment of the spatio-temporal transferability of glacier mass and energy balance models

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A reanalysis of one decade of the mass balance series on Hintereisferner, Ötztal Alps, Austria: a detailed view into annual geodetic and glaciological observations

Cited by 5 publications

References 18 publications

On the Automated Mapping of Snow Cover on Glaciers and Calculation of Snow Line Altitudes from Multi-Temporal Landsat Data

On the Automated Mapping of Snow Cover on Glaciers and Calculation of Snow Line Altitudes from Multi-Temporal Landsat Data

The Rofental: a high Alpine research basin (1890–3770 m a.s.l.) in the Ötztal Alps (Austria) with over 150 years of hydrometeorological and glaciological observations

Robust uncertainty assessment of the spatio-temporal transferability of glacier mass and energy balance models

Contact Info

Product

Resources

About

The Rofental: a high Alpine research basin (1890–3770 m a.s.l.) in the Ötztal Alps (Austria) with over 150 years of hydrometeorological and glaciological observations