ALBERT

Description: Records of glacier mass balance represent important data in climate science and their uncertainties affect calculations of sea level rise and other societally relevant environmental projections. In order to reduce and quantify uncertainties in mass balance series obtained by direct glaciological measurements, we present a detailed reanalysis work-flow which was applied to the ten year record (2004 to 2013) of seasonal mass balance of Langenferner, a small glacier in the European Eastern Alps. The approach involves a methodological homogenization of available point values and the creation of pseudo-observations of point mass balance for years and locations without measurements by the application of a process-based model constrained by snow line observations. We examine the uncertainties related to the extrapolation of point data using a variety of methods, and consequently present a more rigorous uncertainty assessment than is usually reported in the literature. Results reveal that the reanalyzed balance record considerably differs from the original one mainly for the first half of the observation period. For annual balances these misfits reach the order of 〉 300 kg m−2 and could primarily be attributed to a lack of measurements in the upper glacier part and to the use of outdated glacier outlines. For winter balances respective differences are smaller (up to 233 kg m−2) and they originate primarily from methodological inhomogeneities in the original series. Remaining random uncertainties in the reanalized series are mainly determined by the extrapolation of point data to the glacier scale and are in the order of ±80 kg m−2 for annual and ±52 kg m−2 for winter balances with values for single years/seasons reaching ±13 kg m−2. A comparison of the glaciological results to those obtained by the geodetic method for the period 2005 to 2013 based on airborne laser scanning data, reveals that no significant bias of the reanalyzed record is detectable.

Description: Distributed mass balance models, which translate micrometeorological conditions into local melt rates, have proven deficient to reflect the energy flux variability on mountain glaciers. This deficiency is predominantly related to shortcomings in the representation of local processes in the forcing data. We found by means of idealized large-eddy simulations that heat advection, associated with local wind systems, causes small-scale sensible heat flux variations by up to 100 Wm−2 during clear sky conditions. Here we show that process understanding at a few observation sites is insufficient to infer the wind and temperature distributions across the glacier. The glacier-wide hourly averaged sensible heat fluxes are both over- and underestimated by up to 16 Wm−2 when using extrapolated temperature and wind fields. The sign and magnitude of the differences depend on the site selection, which is used for extrapolation as well as on the large-scale flow direction. Our results demonstrate how the shortcomings in the local sensible heat flux estimates are related to topographic effects and the insufficient characterization of the temperature advection process.

Description: Records of glacier mass balance represent important data in climate science and their uncertainties affect calculations of sea level rise and other societally relevant environmental projections. In order to reduce and quantify uncertainties in mass balance series obtained by direct glaciological measurements, we present a detailed reanalysis workflow which was applied to the 10-year record (2004 to 2013) of seasonal mass balance of Langenferner, a small glacier in the European Eastern Alps. The approach involves a methodological homogenization of available point values and the creation of pseudo-observations of point mass balance for years and locations without measurements by the application of a process-based model constrained by snow line observations. We examine the uncertainties related to the extrapolation of point data using a variety of methods and consequently present a more rigorous uncertainty assessment than is usually reported in the literature. Results reveal that the reanalyzed balance record considerably differs from the original one mainly for the first half of the observation period. For annual balances these misfits reach the order of  〉 300 kg m−2 and could primarily be attributed to a lack of measurements in the upper glacier part and to the use of outdated glacier outlines. For winter balances respective differences are smaller (up to 233 kg m−2) and they originate primarily from methodological inhomogeneities in the original series. Remaining random uncertainties in the reanalyzed series are mainly determined by the extrapolation of point data to the glacier scale and are on the order of ±79 kg m−2 for annual and ±52 kg m−2 for winter balances with values for single years/seasons reaching ±136 kg m−2. A comparison of the glaciological results to those obtained by the geodetic method for the period 2005 to 2013 based on airborne laser-scanning data reveals that no significant bias of the reanalyzed record is detectable.

Description: This study presents a reanalysis of the glaciologically obtained annual glacier mass balances at Hintereisferner, Ötztal Alps, Austria, for the period 2001–2011. The reanalysis is accomplished through a comparison with geodetically derived mass changes, using annual high-resolution airborne laser scanning (ALS). The grid-based adjustments for the method-inherent differences are discussed along with associated uncertainties and discrepancies of the two methods of mass balance measurements. A statistical comparison of the two datasets shows no significant difference for seven annual, as well as the cumulative, mass changes over the 10-year record. Yet, the statistical view hides significant differences in the mass balance years 2002/03 (glaciological minus geodetic records  = +0.92 m w.e.), 2005/06 (+0.60 m w.e.), and 2006/07 (−0.45 m w.e.). We conclude that exceptional meteorological conditions can render the usual glaciological observational network inadequate. Furthermore, we consider that ALS data reliably reproduce the annual mass balance and can be seen as validation or calibration tools for the glaciological method.

Description: Energy and mass-balance modelling 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 which 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, extending classical best guess approaches. 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 better constrained parameter choices. The resulting mass balance uncertainties reach up to 1300 kg m−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 parameterizations, 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.

Description: 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 1300kgm−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.