Snow accumulation of a high alpine catchment derived from LiDAR measurements

The spatial distribution of snow accumulation substantially affects the seasonal course of water storage and runoff generation in high mountain catchments. Whereas the areal extent of snow cover can be recorded by satellite data, spatial distribution of snow depth and hence snow water equivalent (SWE) is difficult to measure on catchment scale. In this study we present the application of airborne LiDAR (Light Detecting And Ranging) data to extract snow depths and accumulation distribution in an alpine catchment. <br><br> Airborne LiDAR measurements were performed in a glacierized catchment in the Ötztal Alps at the beginning and the end of three accumulation seasons. The resulting digital elevation models (DEMs) were used to calculate surface elevation changes throughout the winter season. These surface elevation changes were primarily referred to as snow depths and are discussed concerning measured precipitation and the spatial characteristics of the accumulation distribution in glacierized and unglacierized areas. To determine the redistribution of catchment precipitation, snow depths were converted into SWE using a simple regression model. Snow accumulation gradients and snow redistribution were evaluated for 100 m elevation bands. <br><br> Mean surface elevation changes of the whole catchment ranges from 1.97 m to 2.65 m within the analyzed accumulation seasons. By analyzing the distribution of the snow depths, elevation dependent patterns were obtained as a function of the topography in terms of aspect and slope. The high resolution DEMs show clearly the higher variation of snow depths in rough unglacierized areas compared to snow depths on smooth glacier surfaces. Mean snow depths in glacierized areas are higher than in unglacierized areas. Maximum mean snow depths of 100 m elevation bands are found between 2900 m and 3000 m a.s.l. in unglacierized areas and between 2800 m and 2900 m a.s.l. in glacierized areas, respectively. Calculated accumulation gradients range from 8% to 13% per 100 m elevation band in the observed catchment. Elevation distribution of accumulation calculated by applying these seasonal gradients in comparison to elevation distribution of SWE obtained from airborne laser scanning (ALS) data show the total redistribution of snow from higher to lower elevation bands. <br><br> Revealing both, information about the spatial distribution of snow depths and hence the volume of the snow pack, ALS data are an important source for extensive snow accumulation measurements in high alpine catchments. These information about the spatial characteristics of snow distribution are crucial for calibrating hydrological models in order to realistically compute temporal runoff generation by snow melt

Second Austrian Assessment Report on Climate Change (AAR2)

The Second Austrian Assessment Report (AAR2) will provide a comprehensive and inter-disciplinary synthesis of the scientific evidence on climate change in Austria. It will inform policymakers and society at large about synergies and trade-offs of alternative mitigation options and adaptation strategies. The report will be written by more than 150 authors representing the entire Austrian scientific community from all relevant fields and disciplines

DDA1, a novel factor in transcription-coupled repair, modulates CRL4CSA dynamics at DNA damage-stalled RNA polymerase II

Transcription-blocking DNA lesions are specifically targeted by transcription-coupled nucleotide excision repair (TC-NER), which removes a broad spectrum of DNA lesions to preserve transcriptional output and thereby cellular homeostasis to counteract aging. TC-NER is initiated by the stalling of RNA polymerase II at DNA lesions, which triggers the assembly of the TC-NER-specific proteins CSA, CSB and UVSSA. CSA, a WD40-repeat containing protein, is the substrate receptor subunit of a cullin-RING ubiquitin ligase complex composed of DDB1, CUL4A/B and RBX1 (CRL4CSA). Although ubiquitination of several TC-NER proteins by CRL4CSA has been reported, it is still unknown how this complex is regulated. To unravel the dynamic molecular interactions and the regulation of this complex, we applied a single-step protein-complex isolation coupled to mass spectrometry analysis and identified DDA1 as a CSA interacting protein. Cryo-EM analysis showed that DDA1 is an integral component of the CRL4CSA complex. Functional analysis revealed that DDA1 coordinates ubiquitination dynamics during TC-NER and is required for efficient turnover and progression of this process.<br/

Joint Endeavor Toward Sustainable Mountain Development: Research at the Institute for Interdisciplinary Mountain Research of the Austrian Academy of Sciences

The sustainable development of mountain regions requires inter-and transdisciplinary knowledge. The Institute for Interdisciplinary Mountain Research contributes to this global endeavor as part of the Austrian Academy of Sciences and as a member of international scientific networks, together with local partners and stakeholders. As a joint effort of individual researchers covering multiple fields, this article highlights our views on mountains as research objects, the phenomena we investigate as parts of entire mountain systems, and the synergies and differences of the disciplinary frames within which we work

How accurate are estimates of glacier ice thickness? Results from ITMIX, the Ice Thickness Models Intercomparison eXperiment

© Author(s) 2017. Knowledge of the ice thickness distribution of glaciers and ice caps is an important prerequisite for many glaciological and hydrological investigations. A wealth of approaches has recently been presented for inferring ice thickness from characteristics of the surface. With the Ice Thickness Models Intercomparison eXperiment (ITMIX) we performed the first coordinated assessment quantifying individual model performance. A set of 17 different models showed that individual ice thickness estimates can differ considerably - locally by a spread comparable to the observed thickness. Averaging the results of multiple models, however, significantly improved the results: on average over the 21 considered test cases, comparison against direct ice thickness measurements revealed deviations on the order of 10 ± 24% of the mean ice thickness (1σ estimate). Models relying on multiple data sets - such as surface ice velocity fields, surface mass balance, or rates of ice thickness change - showed high sensitivity to input data quality. Together with the requirement of being able to handle large regions in an automated fashion, the capacity of better accounting for uncertainties in the input data will be a key for an improved next generation of ice thickness estimation approaches

Twenty-three unsolved problems in hydrology (UPH) – a community perspective

This paper is the outcome of a community initiative to identify major unsolved scientific problems in hydrology motivated by a need for stronger harmonisation of research efforts. The procedure involved a public consultation through on-line media, followed by two workshops through which a large number of potential science questions were collated, prioritised, and synthesised. In spite of the diversity of the participants (230 scientists in total), the process revealed much about community priorities and the state of our science: a preference for continuity in research questions rather than radical departures or redirections from past and current work. Questions remain focussed on process-based understanding of hydrological variability and causality at all space and time scales. Increased attention to environmental change drives a new emphasis on understanding how change propagates across interfaces within the hydrological system and across disciplinary boundaries. In particular, the expansion of the human footprint raises a new set of questions related to human interactions with nature and water cycle feedbacks in the context of complex water management problems. We hope that this reflection and synthesis of the 23 unsolved problems in hydrology will help guide research efforts for some years to come

Local reduction of decadal glacier thickness loss through mass balance management in ski resorts

For Austrian glacier ski resorts, established in the 1970s and 1980s during a period of glacier advance, negative mass balances with resulting glacier area loss and decrease in surface elevation present an operational challenge. Glacier cover, snow farming, and technical snow production were introduced as adaptation measures based on studies on the effect of these measures on energy and mass balance. After a decade of the application of the various measures, we studied the transition from the proven short-term effects of the measures on mass balance to long-term effects on elevation changes. Based on lidar digital elevation models and differential GPS measurements, decadal surface elevation changes in 15 locations with mass balance management were compared to those without measures (apart from piste grooming) in five Tyrolean ski resorts on seven glaciers. The comparison of surface elevation changes presents clear local differences in mass change, and it shows the potential to retain local ice thickness over 1 decade. Locally up to 21.1 m ± 0.4 m of ice thickness was preserved on mass balance managed areas compared to non-maintained areas over a period of 9 years. In this period, mean annual thickness loss in 15 of the mass balance managed profiles is 0.54 ± 0.04 m yr⁻¹ lower (&minus;0.23 ± 0.04 m yr⁻¹on average) than in the respective reference areas (&minus;0.78 ± 0.04 m yr⁻¹). <br><br> At two of these profiles the surface elevation was preserved altogether, which is promising for a sustainable maintenance of the infrastructure at glacier ski resorts. In general the results demonstrate the high potential of the combination of mass balance management by snow production and glacier cover, not only in the short term but also for multi-year application to maintain the skiing infrastructure

The Cryosphere / Lidar snow cover studies on glaciers in the Ötztal Alps (Austria) : comparison with snow depths calculated from GPR measurements

The storage of water within the seasonal snow cover is a substantial source of runoff in high mountain catchments. Information about the spatial distribution of snow accumulation is necessary for calibration and validation of hydro-meteorological models. Generally, only a small number of precipitation measurements deliver precipitation input for modelling in mountain areas. The spatial interpolation and extrapolation of measurements of precipitation is still difficult. Multi-temporal application of lidar techniques from aircraft, so-called airborne laser scanning (ALS), provides surface elevations changes even in inaccessible terrain. These ALS surface elevation changes can be used to derive changes in snow depths of the mountain snow cover for seasonal or subseasonal time periods. However, since glacier surfaces are not static over time, ablation, densification of snow, densification of firn and ice flow contribute to surface elevation changes. ALS-derived surface elevation changes were compared to snow depths derived from 35.4 km of ground penetrating radar (GPR) profiles on four glaciers. With this combination of two different data acquisitions, it is possible to evaluate the effect of the summation of these processes on ALS-derived snow depth maps in the high alpine region of the Ötztal Alps (Austria). A Landsat 5 Thematic Mapper image was used to distinguish between snow covered area and bare ice areas of the glaciers at the end of the ablation season. In typical accumulation areas, ALS surface elevation changes differ from snow depths calculated from GPR measurements by 0.4 m on average with a mean standard deviation of 0.34 m. Differences between ALS surface elevation changes and GPR derived snow depths are small along the profiles conducted in areas of bare ice. In these areas, the mean absolute difference of ALS surface elevation changes and GPR snow depths is 0.004 m with a standard deviation of 0.27 m. This study presents a systematic approach to analyze deviations from ALS generated snow depth maps to ground truth measurements on four different glaciers. We could show that ALS can be an important and reliable data source for the spatial distribution of snow depths for most parts of the here investigated glaciers. However, within accumulation areas, just utilizing ALS data may lead to systematic underestimation of total snow depth distribution.K. Helfricht, M. Kuhn, M. Keuschnig, and A. Heili

Multilevel spatiotemporal validation of snow/ice mass balance and runoff modeling in glacierized catchments

In this study, the fully distributed, physically based hydroclimatological model AMUNDSEN is set up for catchments in the highly glacierized Ötztal Alps (Austria, 558km2 in total). The model is applied for the period 1997-2013, using a spatial resolution of 50m and a temporal resolution of 1h. A novel parameterization for lateral snow redistribution based on topographic openness is presented to account for the highly heterogeneous snow accumulation patterns in the complex topography of the study region. Multilevel spatiotemporal validation is introduced as a systematic, independent, complete, and redundant validation procedure based on the observation scale of temporal and spatial support, spacing, and extent. This new approach is demonstrated using a comprehensive set of eight independent validation sources: (i) mean areal precipitation over the period 1997-2006 derived by conserving mass in the closure of the water balance, (ii) time series of snow depth recordings at the plot scale, (iii-iv) multitemporal snow extent maps derived from Landsat and MODIS satellite data products, (v) the snow accumulation distribution for the winter season 2010/2011 derived from airborne laser scanning data, (vi) specific surface mass balances for three glaciers in the study area, (vii) spatially distributed glacier surface elevation changes for the entire area over the period 1997-2006, and (viii) runoff recordings for several subcatchments. The results indicate a high overall model skill and especially demonstrate the benefit of the new validation approach. The method can serve as guideline for systematically validating the coupled components in integrated snow-hydrological and glacio-hydrological models.(VLID)3024683Version of recor

Obtaining sub-daily new snow density from automated measurements in high mountain regions

The density of new snow is operationally monitored by meteorological or hydrological services at daily time intervals, or occasionally measured in local field studies. However, meteorological conditions and thus settling of the freshly deposited snow rapidly alter the new snow density until measurement. Physically based snow models and nowcasting applications make use of hourly weather data to determine the water equivalent of the snowfall and snow depth. In previous studies, a number of empirical parameterizations were developed to approximate the new snow density by meteorological parameters. These parameterizations are largely based on new snow measurements derived from local in situ measurements. In this study a data set of automated snow measurements at four stations located in the European Alps is analysed for several winter seasons. Hourly new snow densities are calculated from the height of new snow and the water equivalent of snowfall. Considering the settling of the new snow and the old snowpack, the average hourly new snow density is 68 kg m−3, with a standard deviation of 9 kg m−3. Seven existing parameterizations for estimating new snow densities were tested against these data, and most calculations overestimate the hourly automated measurements. Two of the tested parameterizations were capable of simulating low new snow densities observed at sheltered inner-alpine stations. The observed variability in new snow density from the automated measurements could not be described with satisfactory statistical significance by any of the investigated parameterizations. Applying simple linear regressions between new snow density and wet bulb temperature based on the measurements' data resulted in significant relationships (r2 &gt; 0.5 and p  ≤  0.05) for single periods at individual stations only. Higher new snow density was calculated for the highest elevated and most wind-exposed station location. Whereas snow measurements using ultrasonic devices and snow pillows are appropriate for calculating station mean new snow densities, we recommend instruments with higher accuracy e.g. optical devices for more reliable investigations of the variability of new snow densities at sub-daily intervals.</p