A decade of energy and mass balance investigations on the glacier Kongsvegen, Svalbard

Kongsvegen is an Arctic glacier located in northwest Spitzbergen. We use meteorological observations made near the average equilibrium line of Kongsvegen during the decade 2001 to 2010 to drive a glacier energy and mass balance model. Average daily and seasonal cycles are analyzed over the course of a full decade, as well as the interannual variations of the meteorological parameters and of the mass and energy balance components. The calculated average of net radiation is close to zero and the sensible heat flux is the most important and continuous source of energy at the surface. The latent heat flux is a weak source of energy as well. The resultant flux constellation yields a surplus of energy accumulating throughout the decade (9.5 W m-2) and fosters a negative specific surface mass balance throughout the investigated decade (-1.8 m w. eq.). The most significant mass loss occurred during the middle of the decade (2004 until 2006), with positive surface mass balances observed afterward when significant amounts of superimposed ice were formed. This development is well correlated to the total surface mass balance of the glacier. Application of monthly temperature and precipitation perturbations corroborates earlier studies indicating a high sensitivity of the mass balance to energy fluxes depending on temperature conditions during summer. Key PointsEvaluation of a decadal meteorological record of an Arctic glacierUse of SOMARS, validation of results, investigations of climate sensitiviyAnnual, monthly, daily consideration ©2012. American Geophysical Union. All Rights Reserved

Seasonal streamflow forecasts for Europe – Part I: Hindcast verification with pseudo- and real observations

Seasonal predictions of river flow can be exploited among others to optimise hydropower energy generation, navigability of rivers and irrigation management to decrease crop yield losses. This paper is the first of two papers dealing with a physical model-based system built to produce probabilistic seasonal hydrological forecasts, applied here to Europe. This paper presents the development of the system and the evaluation of its skill. The variable infiltration capacity (VIC) hydrological model is forced with bias-corrected output of ECMWF's seasonal forecast system 4. For the assessment of skill, we analysed hindcasts (1981–2010) against a reference run, in which VIC was forced by gridded meteorological observations. The reference run was also used to generate initial hydrological conditions for the hindcasts.The skill in run-off and discharge hindcasts is analysed with monthly temporal resolution, up to 7 months of lead time, for the entire annual cycle. Using the reference run output as pseudo-observations and taking the correlation coefficient as metric, hot spots of significant theoretical skill in discharge and run-off were identified in Fennoscandia (from January to October), the southern part of the Mediterranean (from June to August), Poland, northern Germany, Romania and Bulgaria (mainly from November to January), western France (from December to May) and the eastern side of Great Britain (January to April). Generally, the skill decreases with increasing lead time, except in spring in regions with snow-rich winters. In some areas some skill persists even at the longest lead times (7 months).Theoretical skill was compared to actual skill as determined with real discharge observations from 747 stations. Actual skill is generally substantially less than theoretical skill. This effect is stronger for small basins than for large basins. Qualitatively, the use of different skill metrics (correlation coefficient; relative operating characteristics, ROC, area; and ranked probability skill score, RPSS) leads to broadly similar spatio-temporal patterns of skill, but the level of skill decreases, and the area of skill shrinks, in the following order: correlation coefficient; ROC area below-normal (BN) tercile; ROC area above-normal (AN) tercile; ranked probability skill score; and, finally, ROC near-normal (NN) tercile

Evaluation of a high-resolution regional climate simulation over Greenland

A simulation of the 1991 summer has been performed over south Greenland with a coupled atmosphere–snow regional climate model (RCM) forced by the ECMWF re-analysis. The simulation is evaluated with in-situ coastal and ice-sheet atmospheric and glaciological observations. Modelled air temperature, specific humidity, wind speed and radiative fluxes are in good agreement with the available observations, although uncertainties in the radiative transfer scheme need further investigation to improve the model’s performance. In the sub-surface snow-ice model, surface albedo is calculated from the simulated snow grain shape and size, snow depth, meltwater accumulation, cloudiness and ice albedo. The use of snow metamorphism processes allows a realistic modelling of the temporal variations in the surface albedo during both melting periods and accumulation events. Concerning the surface albedo, the main finding is that an accurate albedo simulation during the melting season strongly depends on a proper initialization of the surface conditions which mainly result from winter accumulation processes. Furthermore, in a sensitivity experiment with a constant 0.8 albedo over the whole ice sheet, the average amount of melt decreased by more than 60%, which highlights the importance of a correctly simulated surface albedo. The use of this coupled atmosphere–snow RCM offers new perspectives in the study of the Greenland surface mass balance due to the represented feedback between the surface climate and the surface albedo, which is the most sensitive parameter in energy-balance-based ablation calculations.Peer reviewe

A new albedo parameterization for use in climate models over the Antarctic ice sheet

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95255/1/jgrd16889.pd

Fate of water pumped from underground and contributions to sea-level rise

The contributions from terrestrial water sources to sea-level rise, other than ice caps and glaciers, are highly uncertain and heavily debated.. Recent assessments indicate that groundwater depletion (GWD) may become the most important positive terrestrial contribution over the next 50 years, probably equal in magnitude to the current contributions from glaciers and ice caps6. However, the existing estimates assume that nearly 100% of groundwater extracted eventually ends up in the oceans. Owing to limited knowledge of the pathways and mechanisms governing the ultimate fate of pumped groundwater, the relative fraction of global GWD that contributes to sea-level rise remains unknown. Here, using a coupled climate–hydrological model simulation, we show that only 80% of GWD ends up in the ocean. An increase in runoff to the ocean accounts for roughly two-thirds, whereas the remainder results from the enhanced net flux of precipitation minus evaporation over the ocean, due to increased atmospheric vapour transport from the land to the ocean. The contribution of GWD to global sea-level rise amounted to 0.02 (±0.004) mm yr−1 in 1900 and increased to 0.27 (±0.04) mm yr−1 in 2000. This indicates that existing studies have substantially overestimated the contribution of GWD to global sea-level rise by a cumulative amount of at least 10 mm during the twentieth century and early twenty-first century. With other terrestrial water contributions included, we estimate the net terrestrial water contribution during the period 1993–2010 to be +0.12 (±0.04) mm yr−1, suggesting that the net terrestrial water contribution reported in the IPCC Fifth Assessment Report report is probably overestimated by a factor of three

Assessment of the surface mass balance along the K-transect (Greenland ice sheet) from satellite-derived albedos

This paper explores the potential of using satellite-derived albedos to estimate the surface mass balance of the Kangerlussuaq transect (K-transect; Greenland ice sheet). We first retrieved surface albedos from Advanced Very High Resolution Radar data by using, among other techniques, a new cloud detection algorithm based on the relation between brightness temperature and surface elevation. We then computed the ‘satellite-derived mass balance’ (bsat) from the mean albedo for the transect, by taking fixed values for atmospheric transmissivity and the longwave and turbulent fluxes. We found that bsat explains 71% of the variance in 13 years of stake mass-balance measurements (bm). Our method also provides good estimates of the magnitude of the interannual variability in bm. The performance of the method degrades considerably without correction for anisotropic reflection at the surface and recalibration of the satellite sensors with dry snow at the top of the ice sheet. Sensitivity tests indicate that the method’s performance is hardly sensitive to uncertainties in parameters. Therefore, we expect that the method could be successfully applied on other glaciers and parts of ice sheets and ice caps, especially where accumulation rates are relatively small. We show that the investigated method performs best just below the mean equilibrium-line altitude

Validation of AVHRR- and MODIS-derived albedos of snow and ice surfaces by means of helicopter measurements

We describe the validation of surface albedos of snow and glacier ice as derived from Advanced Very High Resolution Radiometer (AVHRR) and MOderate Resolution Imaging Spectrometer (MODIS) satellite data. For this purpose we measured surface albedos from a helicopter over Vatnajökull, Iceland, and the Kangerlussuaq transect (western part of the Greenland ice sheet) in Thematic Mapper (TM) bands 2 and 4 and AVHRR bands 1 and 2, and converted these values to 'measured albedos' in three MODIS bands. Relative to other validation methods, our helicopter measurements have the advantages of larger spatial coverage and of (almost) direct measurements in satellite-sensor spectral bands. We found the smallest differences between the satellite-derived and helicopter albedos for the Kangerlussuaq transect: for AVHRR data a mean difference of 0.01 in both bands (with the satellite in near-nadir position) and for two MODIS images a mean difference of 0.00-0.02 for bands 2 and 4, and 0.03 for band 1. For two AVHRR images of Vatnajökull, we found mean differences of up to 0.06. Differences are primarily due to errors in the satellite-derived albedos, which, in turn, are mainly caused by errors in the calibration coefficients of the satellite sensors and insufficient knowledge of the angular distribution of the radiation reflected by snow and ice. Satellite data obtained from view zenith angles larger than ~50-55° appeared to be unsuitable