Search

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.

Due to 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 for the Rhine basin are used to force a macro-scale hydrological model. These climate scenarios are based on model output from the ECHAM5/MPIOM global climate model, which is in turn forced by three 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 21st 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, that of streamflow droughts only during the second half of the century.

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

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

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

Het is de verwachting dat klimaatverandering een grote invloed zal hebben op de waterhuishouding van stroomgebieden. Toenemende extreme neerslaggebeurtenissen, langere droge periodes en afnemende buffering door sneeuw kunnen leiden tot zowel frequentere en hevigere piekafvoeren als ernstiger droogtes. Landgebruiksveranderingen kunnen deze ontwikkelingen versterken door verstedelijking of tegengaan door bijvoorbeeld bebossing. In dit onderzoek zijn de effecten van zowel klimaat- als landgebruiksveranderingen op de afvoer in het Rijnstroomgebied gekwantificeerd met een hoge ruimtelijke resolutie. Hiertoe is een ruimtelijk gedetailleerd hydrologisch model opgezet, dat op een fysisch-gebaseerde manier uitwisselingen tussen land en atmosfeer simuleert. Met dit model zijn scenarios van landgebruiks- en klimaatveranderingen, gebaseerd op verschillende maatschappelijke ontwikkelingen met daaraan gerelateerde CO2-emissies, doorgerekend. De resultaten tonen drastische veranderingen in het afvoerregime van de Rijn: meer afvoer en hogere piekafvoeren in het voorjaar en, vooral tegen het einde van de eeuw, frequentere en ernstigere afvoerdroogtes in de zomer. Landgebruiksveranderingen hebben daarentegen slechts een gering effect of de afvoer bij Lobith, maar lokaal kunnen de effecten aanzienlijk zijn

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