Ulrich Strasser

Evaluation of forest snow processes models (SnowMIP2)

Thirty-three snowpack models of varying complexity and purpose were evaluated across a wide range of hydrometeorological and forest canopy conditions at five Northern Hemisphere locations, for up t ...

An enhanced temperature-index glacier melt model including the shortwave radiation balance : development and testing for Haut Glacier d'Arolla, Switzerland

An enhanced temperature-index glacier melt model, incorporating incoming shortwave radiation and albedo, is presented. The model is an attempt to combine the high temporal resolution and accuracy of physically based melt models with the lower data requirements and computational simplicity of empirical melt models, represented by the ‘degree-day’ method and its variants. The model is run with both measured and modelled radiation data, to test its applicability to glaciers with differing data availability. Five automatic weather stations were established on Haut Glacier d’Arolla, Switzerland, between May and September 2001. Reference surface melt rates were calculated using a physically based energy-balance melt model. The performance of the enhanced temperature-index model was tested at each of the four validation stations by comparing predicted hourly melt rates with reference melt rates. Predictions made with three other temperature-index models were evaluated in the same way for comparison. The enhanced temperature-index model offers significant improvements over the other temperature-index models, and accounts for 90–95% of the variation in the reference melt rate. The improvement is lower, but still significant, when the model is forced by modelled shortwave radiation data, thus offering a better alternative to existing models that require only temperature data input.

Validation of the energy budget of an alpine snowpack simulated by several snow models (SnowMIP project)

Abstract Many snow models have been developed for various applications such as hydrology, global atmospheric circulation models and avalanche forecasting. The degree of complexity of these models is highly variable, ranging from simple index methods to multi-layer models that simulate snow-cover stratigraphy and texture. In the framework of the Snow Model Intercomparison Project (SnowMIP), 23 models were compared using observed meteorological parameters from two mountainous alpine sites. The analysis here focuses on validation of snow energy-budget simulations. Albedo and snow surface temperature observations allow identification of the more realistic simulations and quantification of errors for two components of the energy budget: the net short- and longwave radiation. In particular, the different albedo parameterizations are evaluated for different snowpack states (in winter and spring). Analysis of results during the melting period allows an investigation of the different ways of partitioning the energy fluxes and reveals the complex feedbacks which occur when simulating the snow energy budget. Particular attention is paid to the impact of model complexity on the energy-budget components. The model complexity has a major role for the net longwave radiation calculation, whereas the albedo parameterization is the most significant factor explaining the accuracy of the net shortwave radiation simulation.

Performance of complex snow cover descriptions in a distributed hydrological model system: A case study for the high Alpine terrain of the Berchtesgaden Alps.

[1] Runoff generation in Alpine regions is typically affected by snow processes. Snow accumulation, storage, redistribution, and ablation control the availability of water. In this study, several robust parameterizations describing snow processes in Alpine environments were implemented in a fully distributed, physically based hydrological model. Snow cover development is simulated using different methods from a simple temperature index approach, followed by an energy balance scheme, to additionally accounting for gravitational and wind-driven lateral snow redistribution. Test site for the study is the Berchtesgaden National Park (Bavarian Alps, Germany) which is characterized by extreme topography and climate conditions. The performance of the model system in reproducing snow cover dynamics and resulting discharge generation is analyzed and validated via measurements of snow water equivalent and snow depth, satellite-based remote sensing data, and runoff gauge data. Model efficiency (the Nash-Sutcliffe coefficient) for simulated runoff increases from 0.57 to 0.68 in a high Alpine headwater catchment and from 0.62 to 0.64 in total with increasing snow model complexity. In particular, the results show that the introduction of the energy balance scheme reproduces daily fluctuations in the snowmelt rates that trace down to the channel stream. These daily cycles measured in snowmelt and resulting runoff rates could not be reproduced by using the temperature index approach. In addition, accounting for lateral snow transport changes the seasonal distribution of modeled snowmelt amounts, which leads to a higher accuracy in modeling runoff characteristics.

Modeling Snow–Canopy Processes on an Idealized Mountain

AbstractSnow interception in a coniferous forest canopy is an important hydrological feature, producing complex mass and energy exchanges with the surrounding atmosphere and the snowpack below. Subcanopy snowpack accumulation and ablation depends on the effects of canopy architecture on meteorological conditions and on interception storage by stems, branches, and needles. Mountain forests are primarily composed of evergreen conifer species that retain their needles throughout the year and hence intercept snow efficiently during winter. Canopy-intercepted snow can melt, fall to the ground, and/or sublimate into the air masses above and within the canopy. To improve the understanding of snow–canopy interception processes and the associated influences on the snowpack below, a series of model experiments using a detailed, physically based snow–canopy and snowpack evolution model [Alpine Multiscale Numerical Distributed Simulation Engine (AMUNDSEN)] driven with observed meteorological forcing was conducted. A ...

The Berchtesgaden National Park (Bavaria, Germany): a platform for interdisciplinary catchment research

The Berchtesgaden National Park (Bavaria, Germany), a study site of the UNESCO Man and the Biosphere program in the catchment of Berchtesgadener Ache, is introduced as a platform for interdisciplinary research. As the investigation of how human activities affect the natural resources in the park area, which has been defined a main aim of the program, naturally requires expertise from different scientific fields, interdisciplinary research has been fostered in the national park plan since the very beginning of the Man and the Biosphere program in 1981. To analyze the complex interactions and mutual dependencies between socio-economic and natural systems, a variety of monitoring programs have been initialized in different disciplines (e.g. climate sciences, zoology, botany) that are addressed in this paper. As a result of these research efforts, the park offers a profound data basis to be used in future studies (e.g. land cover classifications, maps of geological and soil conditions). Detailed information is provided on a climate monitoring network that has been installed in the park starting in the year 1993. The network has been continuously extended over the years and now provides extraordinary comprehensive information on meteorological conditions in the park, setting the basis for current as well as for potential future climate-related studies. A special characteristic of the station network is the fact that it covers a large range of elevations from 600 m a.s.l in the valleys to 2,600 m a.s.l in the summit regions and is therefore able to capture altitudinal gradients in meteorological variables as typical for Alpine regions. Due to the large number of stations in high elevations (15 stations are in elevations higher than 1,500 m a.s.l) the network provides information on the complex hydrometeorological conditions in summit regions which are often insufficiently represented in observation networks due to the increased costs for maintenance of climate stations in these locations. Beside the various monitoring programs, a variety of numerical models have been (further) developed for application in the park area that make extensive use of the different data collected and therefore largely benefit from the comprehensive data pool. The potential and necessity of the climate monitoring network for modelling studies is demonstrated by utilizing the meteorological recordings in the framework of a hydrometeorological simulation experiment. Further examples of environmental modelling efforts are shortly described together with preliminary model results.

Coupled component modelling for inter- and transdisciplinary climate change impact research: Dimensions of integration and examples of interface design

In environmental research the importance of interfaces between the traditional knowledge fields in natural and social sciences is increasingly recognized. In coupled component modelling, the process of developing interface designs can support the communicative, social and cognitive integration between representatives of different knowledge fields. The task of integration is thereby not merely an additive procedure but has to be considered as important part of the research process. In our application, the development of a coupled component model facilitated an integrative assessment of the impact of climate change on snow conditions and skiing tourism in a typical Austrian ski resort. We elaborate the integration on two abstraction levels, a theoretical one and an applied one related to the case study. Other than model output, results presented here relate to the inter- and transdisciplinary development of the coupled component model and its interface design. We show how scientists from various disciplines and representatives from diverse societal fields jointly design interface tools. We identify joint model development - taking into consideration the different dimensions of integration - and recursive modelling as keys for successful inter- and transdisciplinary integration. Such integrative interface science can provide new insights which go beyond the sum of what can be learned from its disciplinary components.

Application of a hydrometeorological model chain to investigate the effect of global boundaries and downscaling on simulated river discharge

In the current study, two regional climate models (MM5 and REMO) driven by different global boundary conditions (the ERA40 reanalysis and the ECHAM5 model) are one-way coupled to the uncalibrated hydrological process model PROMET to analyze the impact of global boundary conditions, dynamical regionalization and subsequent statistical downscaling (bilinear interpolation, correction of subgrid-scale variability and combined correction of subgrid-scale variability and bias) on river discharge simulation. The results of 12 one-way coupled model runs, set up for the catchment of the Upper Danube (Central Europe) over the historical period 1971–2000, prove the expectation that the global boundaries applied to force the RCMs strongly influence the accuracy of simulated river discharge. It is, however, noteworthy that all efficiency criteria in case of bias corrected MM5 simulations indicate better performance under ERA40 boundaries, whereas REMO-driven hydrological simulations better correspond to measured discharge under ECHAM5 boundaries. Comparing the hydrological results achievable with MM5 and REMO, the application of bias-corrected MM5 simulations turned out to allow for a more accurate simulation of discharge, while the variance in simulated discharge in most cases was better reflected in case of REMO forcings. The correction of subgrid-scale variability within the downscaling of RCM simulations compared to a bilinear interpolation allows for a more accurate simulation of discharge for all model configurations and all discharge criteria considered (mean monthly discharge, mean monthly low-flow and peak-flow discharge). Further improvements in the hydrological simulations could be achieved by eliminating the biases (in terms of deviations from observed meteorological conditions) inherent in the driving RCM simulations, regardless of the global boundary conditions or the RCM applied. In spite of all downscaling and bias correction efforts described, the RCM-driven hydrological simulations remain less accurate than those achievable with spatially distributed meteorological observations.

A joint modelling framework for daily extremes of river discharge and precipitation in urban areas

Human settlements are often at risk from multiple hydro-meteorological hazards, which include fluvial floods, short-time extreme precipitation (leading to ‘pluvial’ floods) or coastal floods. In th ...

Large Scale Distributed Hydrological Modelling

The impact of climate change on water resources is one of the most essential issues for the population of mountain areas and their forelands in the future. To identify appropriate adaptation strategies, water balance models must realistically describe and quantify the reactions of watersheds to climate change at the regional scale.