We present a new bed elevation dataset for Greenland derived from a combination of multiple airborne ice thickness surveys undertaken between the 1970s and 2012. Around 420 000 line kilometres of airborne data were used, with roughly 70% of this having been collected since the year 2000, when the last comprehensive compilation was undertaken. The airborne data were combined with satellite-derived elevations for non-glaciated terrain to produce a consistent bed digital elevation model (DEM) over the entire island including across the glaciated–ice free boundary. The DEM was extended to the continental margin with the aid of bathymetric data, primarily from a compilation for the Arctic. Ice thickness was determined where an ice shelf exists from a combination of surface elevation and radar soundings. The across-track spacing between flight lines warranted interpolation at 1 km postings for significant sectors of the ice sheet. Grids of ice surface elevation, error estimates for the DEM, ice thickness and data sampling density were also produced alongside a mask of land/ocean/grounded ice/floating ice. Errors in bed elevation range from a minimum of ±10 m to about ±300 m, as a function of distance from an observation and local topographic variability. A comparison with the compilation published in 2001 highlights the improvement in resolution afforded by the new datasets, particularly along the ice sheet margin, where ice velocity is highest and changes in ice dynamics most marked. We estimate that the volume of ice included in our land-ice mask would raise mean sea level by 7.36 m, excluding any solid earth effects that would take place during ice sheet decay

Because of global warming, the hydrologic behavior of the Rhine basin is expected to shift from a combined snowmelt- and rainfall-driven regime to a more rainfall-dominated regime. Previous impact assessments have indicated that this leads, on average, to increasing streamflow by ∼30% in winter and spring and decreasing streamflow by a similar value in summer. In this study, high-resolution (0.088°) regional climate scenarios conducted with the regional climate model REMO (REgional MOdel) for the Rhine basin are used to force a macroscale hydrological model. These climate scenarios are based on model output from the ECHAM5–Max Planck Institute Ocean Model (MPI-OM) global climate model, which is in turn forced by three Special Report on Emissions Scenarios (SRES) emission scenarios: A2, A1B, and B1. The Variable Infiltration Capacity model (VIC; version 4.0.5) is used to examine changes in streamflow at various locations throughout the Rhine basin. Average streamflow, peak flows, low flows, and several water balance terms are evaluated for both the first and second half of the twenty-first century. The results reveal a distinct contrast between those periods. The first half is dominated by increased precipitation, causing increased streamflow throughout the year. During the second half of the century, a streamflow increase in winter/spring and a decrease in summer is found, similar to previous studies. This is caused by 1) temperature and evapotranspiration, which are considerably higher during the second half of the century; 2) decreased precipitation in summer; and 3) an earlier start of the snowmelt season. Magnitudes of peak flows increase during both periods, and the magnitudes of streamflow droughts increase only during the second half of the century.

Global warming is predicted to have a profound impact on the Greenland Ice Sheet and its contribution to global sea-level rise. Recent mass loss in the northwest of Greenland has been substantial. Using aerial photographs, we produced digital elevation models and extended the time record of recent observed marginal dynamic thinning back to the mid-1980s. We reveal two independent dynamic ice loss events on the northwestern Greenland Ice Sheet margin: from 1985 to 1993 and 2005 to 2010, which were separated by limited mass changes. Our results suggest that the ice mass changes in this sector were primarily caused by short-lived dynamic ice loss events rather than changes in the surface mass balance. This finding challenges predictions about the future response of the Greenland Ice Sheet to increasing global temperatures.

Abstract. In many climate impact studies hydrological models are forced with meteorological data without an attempt to assess the quality of these data. The objective of this study was to compare downscaled ERA15 (ECMWF-reanalysis data) precipitation and temperature with observed precipitation and temperature and apply a bias correction to these forcing variables. Precipitation is corrected by fitting it to the mean and coefficient of variation (CV) of the observations. Temperature is corrected by fitting it to the mean and standard deviation of the observations. It appears that the uncorrected ERA15 is too warm and too wet for most of the Rhine basin. The bias correction leads to satisfactory results, precipitation and temperature differences decreased significantly, although there are a few years for which the correction of precipitation is less satisfying. Corrections were largest during summer for both precipitation and temperature. For precipitation alone large corrections were applied during September and October as well. Besides the statistics the correction method was intended to correct for, it is also found to improve the correlations for the fraction of wet days and lag-1 autocorrelations between ERA15 and the observations. For the validation period temperature is corrected very well, but for precipitation the RMSE of the daily difference between modeled and observed precipitation has increased for the corrected situation. When taking random years for calibration, and the remaining years for validation, the spread in the mean bias error (MBE) becomes larger for the corrected precipitation during validation, but the overal average MBE has decreased.

[1] Accurate streamflow simulations in large river basins are crucial to predict timing and magnitude of floods and droughts and to assess the hydrological impacts of climate change. Water balance models have been used frequently for these purposes. Compared to water balance models, however, land surface models carry the potential to more accurately estimate hydrological partitioning and thus streamflow, because they solve the coupled water and energy balance and are able to exploit a larger part of the information provided by regional climate model output than water balance models. Owing to increased model complexity, however, they are also more difficult to parameterize. The purpose of this study is to investigate and compare the accuracy of streamflow simulations of a water balance approach (Spatial Tools for River basins and Environment and Analysis of Management (STREAM)) and a land surface model (Variable Infiltration Capacity (VIC)) approach. Both models are applied to the Rhine river basin using regional climate model output as atmospheric forcing, and are evaluated using observed streamflow and lysimeter data. We find that VIC is more robust and less dependent on model calibration. Although STREAM performs better during the calibration period (Nash-Sutcliffe efficiency (E) of 0.47 versus E = 0.29 for VIC), VIC more accurately simulates discharge during the validation period, including peak flows (E = 0.31 versus E = 0.21 for STREAM). This is the case for most locations throughout the basin, except for the Alpine part where both models have difficulties due to the complex terrain and surface reservoirs. In addition, the annual evaporation cycle at the lysimeters is more realistically simulated by VIC.