ALBERT

Description: This Article reports results from a field experiment investigating the influence of volcanic tephra coverage on glacier ablation. These influences are known to be significantly different from those of moraine debris on glaciers due to the contrasting grain size distribution and thermal conductivity. Influences of tephra deposits on glacier ablation have hardly been studied so far. For the experiment, artificial plots of two different tephra types from Eyjafjallajökull and Grimsvötn volcanoes were installed on a snow-covered glacier surface of Vatnajökull ice cap, Iceland.Ablation was automatically monitored along with atmospheric variables and ablation on a non-tephra covered reference site over the summer season 2015. For each of the two volcanic tephra types, three plots (~ 1.5 mm, ~ 8.5 mm and ~ 80 mm) were monitored. After limiting the records to a period of reliable measurements, a 50-days dataset of hourly records was obtained, which can be downloaded from the Pangaea data repository (https://www.pangaea.de; https://doi.org/10.1594/PANGAEA.876656). The experiment shows a substantial increase of ablation under the ~ 1.5 mm and ~ 8.5 mm tephra plots when compared to uncovered conditions. Only under the thick tephra cover some insulating effects could be observed. This result is in contrast to other studies which depicted insulating effects for much thinner tephra coverson bare-ice glacier surfaces. Differences between the influences of the two different petrological types of tephra exist but are small.

Description: We report results from a field experiment investigating the influence of volcanic tephra coverage on glacier ablation. These influences are known to be significantly different from those of moraine debris on glaciers due to the contrasting grain size distribution and thermal conductivity. Thus far, the influences of tephra deposits on glacier ablation have rarely been studied. For the experiment, artificial plots of two different tephra types from Eyjafjallajökull and Grímsvötn volcanoes were installed on a snow-covered glacier surface of Vatnajökull ice cap, Iceland. Snow-surface lowering and atmospheric conditions were monitored in summer 2015 and compared to a tephra-free reference site. For each of the two volcanic tephra types, three plots of variable thickness (∼ 1.5, ∼ 8.5 and ∼ 80 mm) were monitored. After limiting the records to a period of reliable measurements, a 50-day data set of hourly records was obtained, which can be downloaded from the Pangaea data repository (https://www.pangaea.de; doi:10.1594/PANGAEA.876656). The experiment shows a substantial increase in snow-surface lowering rates under the ∼ 1.5 and ∼ 8.5 mm tephra plots when compared to uncovered conditions. Under the thick tephra cover some insulating effects could be observed. These results are in contrast to other studies which depicted insulating effects for much thinner tephra coverage on bare-ice glacier surfaces. Differences between the influences of the two different petrological types of tephra exist but are negligible compared to the effect of tephra coverage overall.

Description: Snow depths and bulk densities of the annual snow layer were measured at 69 different locations on glaciers across Nordenskiöldland, Svalbard, during the spring seasons of the period 2014–2016. Sampling locations lie along nine transects extending over 17 individual glaciers. Several of the locations were visited repeatedly, leading to a total of 109 point measurements, on which we report in this study. Snow water equivalents were calculated for each point measurement. In the dataset, snow depth and density measurements are accompanied by appropriate uncertainties which are rigorously transferred to the calculated snow water equivalents using a straightforward Monte Carlo simulation-style procedure. The final dataset can be downloaded from the Pangaea data repository (https://www.pangaea.de; https://doi.org/10.1594/PANGAEA.896581). Snow cover data indicate a general and statistically significant increase of snow depths and water equivalents with terrain elevation. A significant increase of both quantities with decreasing distance towards the east coast of Nordenskiöldland is also evident, but shows distinct interannual variability. Snow density does not show any characteristic spatial pattern.

Description: Many practical applications of statistical post-processing methods for ensemble weather forecasts require accurate modeling of spatial, temporal, and inter-variable dependencies. Over the past years, a variety of approaches has been proposed to address this need. We provide a comprehensive review and comparison of state-of-the-art methods for multivariate ensemble post-processing. We focus on generally applicable two-step approaches where ensemble predictions are first post-processed separately in each margin and multivariate dependencies are restored via copula functions in a second step. The comparisons are based on simulation studies tailored to mimic challenges occurring in practical applications and allow ready interpretation of the effects of different types of misspecifications in the mean, variance, and covariance structure of the ensemble forecasts on the performance of the post-processing methods. Overall, we find that the Schaake shuffle provides a compelling benchmark that is difficult to outperform, whereas the forecast quality of parametric copula approaches and variants of ensemble copula coupling strongly depend on the misspecifications at hand.

Description: An extensive validation of line-of-sight tropospheric slant total delays (STD) from Global Navigation Satellite Systems (GNSS), ray tracing in numerical weather prediction model (NWM) fields and microwave water vapour radiometer (WVR) is presented. Ten GNSS reference stations, including collocated sites, and almost 2 months of data from 2013, including severe weather events were used for comparison. Seven institutions delivered their STDs based on GNSS observations processed using 5 software programs and 11 strategies enabling to compare rather different solutions and to assess the impact of several aspects of the processing strategy. STDs from NWM ray tracing came from three institutions using three different NWMs and ray-tracing software. Inter-techniques evaluations demonstrated a good mutual agreement of various GNSS STD solutions compared to NWM and WVR STDs. The mean bias among GNSS solutions not considering post-fit residuals in STDs was −0.6 mm for STDs scaled in the zenith direction and the mean standard deviation was 3.7 mm. Standard deviations of comparisons between GNSS and NWM ray-tracing solutions were typically 10 mm ± 2 mm (scaled in the zenith direction), depending on the NWM model and the GNSS station. Comparing GNSS versus WVR STDs reached standard deviations of 12 mm ± 2 mm also scaled in the zenith direction. Impacts of raw GNSS post-fit residuals and cleaned residuals on optimal reconstructing of GNSS STDs were evaluated at inter-technique comparison and for GNSS at collocated sites. The use of raw post-fit residuals is not generally recommended as they might contain strong systematic effects, as demonstrated in the case of station LDB0. Simplified STDs reconstructed only from estimated GNSS tropospheric parameters, i.e. without applying post-fit residuals, performed the best in all the comparisons; however, it obviously missed part of tropospheric signals due to non-linear temporal and spatial variations in the troposphere. Although the post-fit residuals cleaned of visible systematic errors generally showed a slightly worse performance, they contained significant tropospheric signal on top of the simplified model. They are thus recommended for the reconstruction of STDs, particularly during high variability in the troposphere. Cleaned residuals also showed a stable performance during ordinary days while containing promising information about the troposphere at low-elevation angles.

Description: Measuring temperature and salinity profiles in the world's oceans is crucial to understanding ocean dynamics and its influence on the heat budget, the water cycle, the marine environment and on our climate. Since 1983 the German research vessel and icebreaker Polarstern has been the platform of numerous CTD (conductivity, temperature, depth instrument) deployments in the Arctic and the Antarctic. We report on a unique data collection spanning 33 years of polar CTD data. In total 131 data sets (1 data set per cruise leg) containing data from 10 063 CTD casts are now freely available at doi:10.1594/PANGAEA.860066. During this long period five CTD types with different characteristics and accuracies have been used. Therefore the instruments and processing procedures (sensor calibration, data validation, etc.) are described in detail. This compilation is special not only with regard to the quantity but also the quality of the data – the latter indicated for each data set using defined quality codes. The complete data collection includes a number of repeated sections for which the quality code can be used to investigate and evaluate long-term changes. Beginning with 2010, the salinity measurements presented here are of the highest quality possible in this field owing to the introduction of the OPTIMARE Precision Salinometer.

Description: The interactions between climate, vegetation and fire can strongly influence the future trajectories of vegetation in Earth system models. We evaluate the relationships between tropical climate, vegetation and fire in the global vegetation model JSBACH, using a simple fire scheme and the complex fire model SPITFIRE with the aim to identify potential for model improvement. We use two remote-sensing products (based on MODIS and Landsat) in different resolutions to assess the robustness of the obtained observed relationships. We evaluate the model using a multivariate comparison that allows us to focus on the interactions between climate, vegetation and fire and test the influence of land use change on the modelled patterns. Climate–vegetation–fire relationships are known to differ between continents; we therefore perform the analysis for each continent separately. The observed relationships are similar in the two satellite data sets, but maximum tree cover is reached at higher precipitation values for coarser resolution. This shows that the spatial scale of models and data needs to be consistent for meaningful comparisons. The model captures the broad spatial patterns with regional differences, which are partly due to the climate forcing derived from an Earth system model. Compared to the simple fire scheme, SPITFIRE strongly improves the spatial pattern of burned area and the distribution of burned area along increasing precipitation. The correlation between precipitation and tree cover is higher in the observations than in the largely climate-driven vegetation model, with both fire models. The multivariate comparison identifies excessive tree cover in low-precipitation areas and a too-strong relationship between high fire occurrence and low tree cover for the complex fire model. We therefore suggest that drought effects on tree cover and the impact of burned area on tree cover or the adaptation of trees to fire can be improved. The observed variation in the relationship between precipitation and maximum tree cover between continents is higher than the simulated one. Land use contributes to the intercontinental differences in fire regimes with SPITFIRE and strongly overprints the modelled multimodality of tree cover with SPITFIRE. The multivariate model–data comparison used here has several advantages: it improves the attribution of model–data mismatches to model processes, it reduces the impact of biases in the meteorological forcing on the evaluation and it allows us to evaluate not only a specific target variable but also the interactions.

Description: Initial objectives and design of the Benchmark campaign organized within the European COST Action ES1206 (2013-2017) are described in the paper. This campaign has aimed at supporting the development and validation of advanced GNSS tropospheric products, in particular high-resolution and ultra-fast zenith total delays (ZTD) and tropospheric gradients derived from a dense permanent network. A complex dataset was collected for the 8-week period when several extreme heavy precipitation episodes occurred in central Europe which caused severe river floods in this area. An initial processing of data sets from Global Navigation Satellite System (GNSS) and numerical weather models (NWM) provided independently estimated reference parameters – zenith tropospheric delays and tropospheric horizontal gradients. Their provision gave an overview about the product similarities and complementarities and thus a potential for improving a synergy in their optimal exploitations in future. Reference GNSS and NWM results were inter-compared and visually analysed using animated maps. ZTDs from two reference GNSS solutions compared to global ERA-Interim re-analysis resulted in the accuracy at the 10-millimeter level in terms of RMS (with a negligible overall bias), comparisons to global GFS forecast showed accuracy at the 12-millimeter level with the overall bias of -5 mm and, finally, comparisons to mesoscale ALADIN-CZ forecast resulted in the accuracy at the 8-milllimetre level with a negligible total bias. The comparison of horizontal tropospheric gradients from GNSS and NWM data demonstrated a very good agreement among independent solutions with negligible biases and the accuracy of about 0.5 mm. Visual comparisons of maps of zenith wet delays and tropospheric horizontal gradients showed very promising results for future exploitations of advanced GNSS tropospheric products in meteorological applications such as severe weather event monitoring and weather nowcasting. The GNSS products revealed a capability of providing more detailed structures in atmosphere than the state-of-the-art numerical weather models are able to capture. Initial study on contribution of hydrometeors (e.g. cloud water, ice or snow) to GNSS signal delays during severe weather reached up to 17 mm in zenith path delay and suggested to carefully account them within the functional model. The reference products will be further exploited in various specific studies using the Benchmark dataset. It is thus going to play a key role in these highly inter-disciplinary developments towards better mutual benefits from advanced GNSS and meteorological products.

Description: A new wave data set from the southern North Sea covering the period 2011–2016 and composed of wave buoy and radar measurements sampling the sea surface height at frequencies between 1.28 and 4 Hz was quality controlled and scanned for the presence of rogue waves. Here, rogue waves refer to waves whose height exceeds twice the significant wave height. Rogue wave frequencies were analyzed and compared to Rayleigh and Forristall distributions, and spatial, seasonal, and long-term variability was assessed. Rogue wave frequency appeared to be relatively constant over the course of the year and uncorrelated among the different measurement sites. While data from buoys basically correspond with expectations from the Forristall distribution, radar measurement showed some deviations in the upper tail pointing towards higher rogue wave frequencies. The amount of data available in the upper tail is, however, still too limited to allow a robust assessment. Some indications were found that the distribution of waves in samples with and without rogue waves was different in a statistical sense. However, differences were small and deemed not to be relevant as attempts to use them as a criterion for rogue wave detection were not successful in Monte Carlo experiments based on the available data.

Description: The redistribution of snow by drifting and blowing snow frequently leads to an inhomogeneous snow mass distribution on larger ice caps. Together with the thermodynamic impact of drifting snow sublimation on the lower atmospheric boundary layer, these processes affect the glacier surface mass balance. This study provides a first quantification of snowdrift and sublimation of blowing and drifting snow on the Vestfonna ice cap (Svalbard) by using the specifically designed snow2blow snowdrift model. The model is forced by atmospheric fields from the Polar Weather Research and Forecasting model and resolves processes on a spatial resolution of 250 m. The model is applied to the Vestfonna ice cap for the accumulation period 2008/2009. Comparison with radio-echo soundings and snow-pit measurements show that important local-scale processes are resolved by the model and the overall snow accumulation pattern is reproduced. The findings indicate that there is a significant redistribution of snow mass from the interior of the ice cap to the surrounding areas and ice slopes. Drifting snow sublimation of suspended snow is found to be stronger during spring. It is concluded that the redistribution process is strong enough to have a significant impact on glacier mass balance.