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In many climate impact studies hydrological models are forced with meteorological forcing data without an attempt to assess the quality of these forcing data. The objective of this study is to compare downscaled ERA15 (ECMWF-reanalysis data) precipitation and temperature with observed precipitation and temperature and apply a bias correction to these forcing variables. The bias-corrected precipitation and temperature data will be used in another study as input for the Variable Infiltration Capacity (VIC) model. Observations were available for 134 sub-basins throughout the Rhine basin at a temporal resolution of one day from the International Commission for the Hydrology of the Rhine basin (CHR). Precipitation is corrected by fitting the mean and coefficient of variation (CV) of the observations. Temperature is corrected by fitting the mean and standard deviation of the observations. It seems 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. Corrections were largest during summer for both precipitation and temperature, and for September and October for precipitation only. 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 more than two decades, radar altimetry missions have provided continuous elevation estimates of the Greenland ice sheet (GrIS). Here, we propose a method for using such data to estimate ice-sheet-wide surface elevation changes (SECs). The final data set will be based on observations acquired from the European Space Agency’s Environmental Satellite (ENVISAT), European Remote Sensing (ERS)-1 and -2, CryoSat-2, and, in the longer term, Sentinel-3 satellites. In order to find the best-performing method, an intercomparison exercise has been carried out in which the scientific community was asked to provide their best SEC estimates as well as feedback sheets describing the applied method. Due to the hitherto few radar-based SEC analyses as well as the higher accuracy of laser data, the participants were asked to use either ENVISAT radar or ICESat (Ice, Cloud, and land Elevation Satellite) laser altimetry over the Jakobshavn Isbræ drainage basin. The submissions were validated against airborne laser-scanner data, and intercomparisons were carried out to analyse the potential of the applied methods and to find whether the two altimeters were capable of resolving the same signal. The analyses found great potential of the applied repeat-track and cross-over techniques, and, for the first time over Greenland, that repeat-track analyses from radar altimetry agreed well with laser data. Since topography-related errors can be neglected in cross-over analyses, it is expected that the most accurate, ice-sheet-wide SEC estimates are obtained by combining the cross-over and repeat-track techniques. It is thus possible to exploit the high accuracy of the former and the large spatial data coverage of the latter. Based on CryoSat’s different operation modes, and the increased spatial and temporal data coverage, this shows good potential for a future inclusion of CryoSat-2 and Sentinel-3 data to continuously obtain accurate SEC estimates both in the interior and margin ice sheet.

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[1] We estimate ice volume change rates in the northwest Greenland drainage basin during 2003‐2009 using Ice, Cloud and land Elevation Satellite (ICESat) laser altimeter data. Elevation changes are often reported to be largest near the frontal portion of outlet glaciers. To improve the volume change estimate, we supplement the ICESat data with altimeter surveys from NASA’s Airborne Topographic Mapper from 2002 to 2010 and NASA’s Land, Vegetation and Ice Sensor from 2010. The Airborne data are mainly concentrated along the ice margin and thus have a significant impact on the estimate of the volume change. Our results show that adding Airborne Topographic Mapper and Land, Vegetation and Ice Sensor data to the ICESat data increases the catchment-wide estimate of ice volume loss by 11%, mainly due to an improved volume loss estimate along the ice sheet margin. Furthermore, our results show a significant acceleration in mass loss at elevations above 1200m. Both the improved mass loss estimate along the ice sheet margin and the acceleration at higher elevations have implications for predictions of the elastic adjustment of the lithosphere caused by present-day ice mass changes. Our study shows that the use of ICESat data alone to predict elastic uplift rates biases the predicted rates by several millimeters per year at GPS locations along the northwestern coast.

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. 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.

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] We solve the sea-level equation to investigate the pattern of the gravitationally self-consistent sea-level variations (fingerprints) corresponding to modeled scenarios of future terrestrial ice melt. These were obtained from separate ice dynamics and surface mass balance models for the Greenland and Antarctic ice sheets and by a regionalized mass balance model for glaciers and ice caps. For our mid-range scenario, the ice melt component of total sea-level change attains its largest amplitude in the equatorial oceans, where we predict a cumulative sea-level rise of ~ 25 cm and rates of change close to 3 mm/yr from ice melt alone by 2100. According to our modeling, in low-elevation densely populated coastal zones, the gravitationally consistent sea-level variations due to continental ice loss will range between 50 and 150% of the global mean. This includes the effects of glacial-isostatic adjustment, which mostly contributes across the lateral forebulge regions in North America. While the mid range ocean-averaged elastic-gravitational sea-level variations compare with those associated with thermal expansion and ocean circulation, their combination shows a complex regional pattern, where the former component dominates in the Equatorial Pacific Ocean and the latter in the Arctic Ocean.

Changes in both global and regional mean sea level, and changes in the magnitude of extreme flood heights, are the result of a combination of several distinct contributions most, but not all, of which are associated with climate change. These contributions include effects in the solid earth, gravity field, changes in ocean mass due to ice loss from ice sheets and glaciers, thermal expansion, alterations in ocean circulation driven by climate change and changing freshwater fluxes, and the intensity of storm surges. Due to the diverse range of models required to simulate these systems, the contributions to sea-level change have usually been discussed in isolation rather than in one self-consistent assessment. Focusing on the coastline of northwest Europe, we consider all the processes mentioned above and their relative impact on 21st century regional mean sea levels and the 50-year return flood height. As far as possible our projections of change are derived from process-based models forced by the A1B emissions scenario to provide a self-consistent comparison of the contributions. We address uncertainty by considering both a mid-range and an illustrative high-end combination of the different components. For our mid-range ice loss scenario we find that thermal expansion of seawater is the dominant contributor to change in northwest European sea level by 2100. However, the projected contribution to extreme sea level, due to changes in storminess alone, is in some places significant and comparable to the global mean contribution of thermal expansion. For example, under the A1B emissions scenario, by 2100, change in storminess contributes around 15 cm to the increase in projected height of the 50-year storm surge on the west coast of the Jutland Peninsula, compared with a contribution of around 22 cm due to thermal expansion and a total of 58 cm from all of the contributions we consider. An illustrative combination of our high-end projections suggests increases in the 50-year return level of 86 cm at Sheerness, 95 cm at Roscoff, 106 cm at Esbjerg, and 67cm at Bergen. The notable regional differences between these locations arise primarily from differences in the rates of vertical land movement and changes in storminess.

In order to increase the understanding of the changing climate, the European Space Agency has launched the Climate Change Initiative (ESA CCI), a program which joins scientists and space agencies into 13 projects either affecting or affected by the concurrent changes. This work is part of the Ice Sheets CCI and four parameters are to be determined for the Greenland Ice Sheet (GrIS), each resulting in a dataset made available to the public: Surface Elevation Changes (SEC), surface velocities, grounding line locations, and calving front locations. All CCI projects have completed a so-called Round Robin exercise in which the scientific community was asked to provide their best estimate of the sought parameters as well as a feedback sheet describing their work. By inter-comparing and validating the results, obtained from research institutions world-wide, it is possible to develop the most optimal method for determining each parameter. This work describes the SEC Round Robin and the subsequent conclusions leading to the creation of a method for determining GrIS SEC values. The participants used either Envisat radar or ICESat laser altimetry over Jakobshavn Isbræ drainage basin, and the submissions led to inter-comparisons of radar vs. altimetry as well as cross-over vs. repeat-track analyses. Due to the high accuracy of the former and the high spatial resolution of the latter, a method, which combines the two techniques will provide the most accurate SEC estimates. The data supporting the final GrIS analysis stem from the radar altimeters on-board Envisat, ERS-1 and ERS-2. The accuracy of laser data exceeds that of radar altimetry; the Round Robin analysis has, however, proven the latter equally capable of dealing with surface topography thereby making such data applicable in SEC analyses extending all the way from the interior ice sheet to margin regions. This shows good potential for a~future inclusion of ESA CryoSat-2 and Sentinel-3 radar data in the analysis, and thus for obtaining reliable SEC estimates throughout the entire GrIS.

We present a new bed elevation dataset for Greenland derived from a combination of multiple airborne ice thickness surveys undertaken between the 1970s and 2011. Around 344 000 line kilometres of airborne data were used, with the majority 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 shelf thickness was determined where a floating tongue exists, in particular in the north. The across-track spacing between flight lines warranted interpolation at 1 km postings near the ice sheet margin and 2.5 km in the interior. 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 ±6 m to about ±200 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 data sets, particularly along the ice sheet margin, where ice velocity is highest and changes most marked. We use the new bed and surface DEMs to calculate the hydraulic potential for subglacial flow and present the large scale pattern of water routing. We estimate that the volume of ice included in our land/ice mask would raise eustatic sea level by 7.36 m, excluding any solid earth effects that would take place during ice sheet decay.

In deriving elevation change rates (dH/dt) from radar altimetry, the slope-induced error is usually assumed to cancel out in repeat measurements. These measurements, however, represent a location that can be significantly further upslope than assumed, causing an underestimate of the basin-integrated volume change. In a case-study for the fast-flowing part of Jakobshavn Isbræ, we show that a relatively straightforward correction for slope-induced error increases elevation change rates by several metres and increases the volume change by 32% for the region of interest.

Estimation of ice sheet mass balance from satellite altimetry requires interpolation of point-scale elevation change (dH/dt) data over the area of interest. The largest dH/dt values occur over narrow, fast-flowing outlet glaciers, where data coverage of current satellite altimetry is poorest. In those areas, straightforward interpolation of data is unlikely to reflect the true patterns of dH/dt. Here, four interpolation methods are compared and evaluated over Jakobshavn Isbræ, an outlet glacier for which widespread airborne validation data are available from NASA's Airborne Topographic Mapper (ATM). The four methods are ordinary kriging (OK), kriging with external drift (KED), where the spatial pattern of surface velocity is used as a proxy for that of dH/dt, and their spatiotemporal equivalents (ST-OK and ST-KED). KED assumes a linear relationship between spatial gradients of velocity and dH/dt, which is confirmed for both negative (Pearson's correlation ρ < −0.85) and, to a lesser degree, positive (ρ = 0.73) dH/dt values. When compared to ATM data, KED and ST-KED yield more realistic spatial patterns and higher thinning rates (over 20 m yr−1 as opposed to 7 m yr−1 for OK). Spatiotemporal kriging smooths inter-annual variability and improves interpolation in periods with sparse data coverage and we conclude, therefore, that ST-KED produces the best results. Using this method increases volume loss estimates from Jakobshavn Isbræ by up to 20% compared to those obtained by OK. The proposed interpolation method will improve ice sheet mass balance reconstructions from existing and past satellite altimeter data sets, with generally poor sampling of outlet glaciers.

The main objective of this work is to identify and evaluate the potential impacts produced by climate and land use changes in six test-bed basins (Llobregat, Guadalhorce, Gardon d'Anduze, Linth, Verzasca and Sambuco). Data to build future scenarios that can modify the different basins' flash flood and debris flow risk level has been analyzed in this report. High resolution climate scenarios have been obtained from several European projects and/or National initiatives, depending on each case. Climatic variables have been widely analysed, with a special focus on extreme precipitation. The importance of using climate data at the maximum spatial and temporal resolution and downscaling methodologies, which have been adapted to basin scale (test-beds areas ranging from approx 200 to 5000 km2) and extreme rainfall values is one of the main conclusions. Typical GEV distributions have been fitted to observed and projected rainfall data in order to assess impacts in the frequency distributions of extreme rainfall up to 2100. Regarding land use changes, a cellular automata-based model has been used (MOLAND) to simulate the 2000-2040 period taking the CORINE land use dataset as input data. Llobregat, Guadalhorce and Gardon d'Anduze basins have been identified as potentially interesting for simulating urban land-use dynamics due to the existence of important urban areas within their limits. The assessment of the rural land-use changes has been carried out using the results from the Eururalis project (2000-2030 period), available for all the basins., JRC.H.7-Climate Risk Management

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.

The Meuse is an important river in Western Europe, which is almost exclusively rain-fed. Projected changes in precipitation characteristics due to climate change, therefore, are expected to have a considerable effect on the hydrological regime of the river Meuse. We focus on an important tributary of the Meuse, the Ourthe, measuring about 1600 km2. The well-known hydrological model HBV is forced with three high-resolution (0.088°) regional climate scenarios, each based on one of three different IPCC CO2 emission scenarios: A1B, A2 and B1. To represent the current climate, a reference model run at the same resolution is used. Prior to running the hydrological model, the biases in the climate model output are investigated and corrected for. Different approaches to correct the distributed climate model output using single-site observations are compared. Correcting the spatially averaged temperature and precipitation is found to give the best results, but still large differences exist between observations and simulations. The bias corrected data are then used to force HBV. Results indicate a small increase in overall discharge, especially for the B1 scenario during the beginning of the 21st century. Towards the end of the century, all scenarios show a decrease in summer discharge, partially because of the diminished buffering effect by the snow pack, and an increased discharge in winter. It should be stressed, however, that we used results from only one GCM (the only one available at such a high resolution). It would be interesting to repeat the analysis with multiple models.

[1] The hydrological regime of the Rhine basin is expected to shift from a combined snowmelt-rainfall regime to a more rainfall-dominated regime because of climate change, leading to more extreme flood peaks and low flows. Land use changes may reinforce the effects of this shift through urbanization or may counteract them through, for example, afforestation. In this study, we investigate the effect of projected land use change scenarios on river discharge. Sensitivity of mean and extreme discharge in the Rhine basin to land use changes is investigated at various spatial scales. The variable infiltration capacity (VIC) (version 4.0.5) model is used for hydrological modeling forced by a high-resolution atmospheric data set spanning the period 1993–2003. The model is modified to allow for bare soil evaporation and canopy evapotranspiration simultaneously in sparsely vegetated areas, as this is more appropriate for simulating seasonal effects. All projected land use change scenarios lead to an increase in streamflow. The magnitude of the increase, however, varies among subbasins of different scales from about 2% in the upstream part of the Rhine (about 60,000 km2) to about 30% in the Lahn basin (about 7000 km2). Streamflow at the basin outlet proved rather insensitive to land use changes because over the entire basin affected areas are relatively small. Moreover, projected land use changes (urbanization and conversion of cropland into (semi)natural land or forest) have opposite effects. At smaller scales, however, the effects can be considerable.

Understanding the long-term (interannual–decadal) variability of water availability in river basins is paramount for water resources management. Here, the authors analyze time series of simulated terrestrial water storage components, observed precipitation, and discharge spanning 74 yr in the Colorado River basin and relate them to climate indices that describe variability of sea surface temperature and sea level pressure in the tropical and extratropical Pacific. El Niño–Southern Oscillation (ENSO) indices in winter [January–March (JFM)] are related to winter precipitation as well as to soil moisture and discharge in the lower Colorado River basin. The low-frequency mode of the Pacific decadal oscillation (PDO) appears to be strongly correlated with deep soil moisture. During the negative PDO phase, saturated storage anomalies tend to be negative and the “amplitudes” (mean absolute anomalies) of shallow soil moisture, snow, and discharge are slightly lower compared to periods of positive PDO phases. Predicting interannual variability, therefore, strongly depends on the capability of predicting PDO regime shifts. If indeed a shift to a cool PDO phase occurred in the mid-1990s, as data suggest, the current dry conditions in the Colorado River basin may persist.

Due to the growing wish and necessity to simulate the possible effects of climate change on the discharge regime on large rivers such as the Rhine in Europe, there is a need for well performing hydrological models that can be applied in climate change scenario studies. There exists large variety in available models and there is an ongoing debate in research on rainfall-runoff modelling on whether or not physically based distributed models better represent observed discharges than conceptual lumped model approaches do. In addition, it is argued that Land Surface Models (LSMs) carry the potential to accurately estimate hydrological partitioning, because they solve the coupled water and energy balance. In this paper, the hydrological models HBV and VIC were compared for the Rhine basin by testing their performance in simulating discharge. Overall, the semi-distributed conceptual HBV model performed much better than the distributed land surface model VIC (E=0.62, r2=0.65 vs. E=0.31, r2=0.54 at Lobith). It is argued here that even for a well-documented river basin such as the Rhine, more complex modelling does not automatically lead to better results. Moreover, it is concluded that meteorological forcing data has a considerable influence on model performance, irrespectively to the type of model structure and the need for ground-based meteorological measurements is emphasized.

[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.

[1] Characterization of the space-time variability of soil moisture is important for land surface and climate studies. Here we develop an analytical model to investigate how, at the dry-end of the soil moisture range, the main characteristics of the soil moisture field (spatial mean and variability, steady state distribution) depend on the intermittent character of low intensity rain storms. Our model is in good agreement with data from the recent National Airborne Field Experiment (NAFE’06) held in the semiarid Australian Murrumbidgee catchment. We find a positive linear relationship between mean soil moisture and its associated variability, and a strong dependency of the temporal soil moisture distribution to the amount and structure of precipitation. Citation: Teuling, A. J., R. Uijlenhoet, R. Hurkmans, O. Merlin, R. Panciera, J. P. Walker, and P. A. Troch (2007), Dry-end surface soil moisture variability during NAFE’06, Geophys. Res. Lett., 34, L17402, doi:10.1029/ 2007GL031001.

The total amount of water stored in a river basin affects streamflow at various timescales and defines the river basin's response to atmospheric forcing. For example, spring runoff in mountainous midlatitude catchments depends on winter snowpack, and groundwater storage sustains flow during dry periods. An accurate estimation of terrestrial water storage (TWS) is thus paramount for improved water management. Direct determination of TWS is difficult due to insufficient in situ data on space-time variability of hydrologic stores (snow, soil moisture, groundwater) and fluxes (precipitation, evapotranspiration). However, alternative methods using new data sets show great potential to improve the estimation of intra-annual and interannual TWS dynamics.