The application of Regional Climate Model output for the simulation of high-mountain permafrost scenarios
Introduction
High-mountain environments in general, and the alpine cryosphere in particular, are affected most seriously by climate change (Haeberli and Beniston, 1998, Smith and Riseborough, 2002, Diaz et al., 2003, Harris et al., 2003, Kääb et al., 2005). The thawing of alpine permafrost can have a severe impact on the stability of rock walls and debris slopes and on engineered structures (Haeberli, 1992, Haeberli et al., 1997, Davies et al., 2001, Harris et al., 2001, Kääb et al., 2005). The extremely hot and dry summer of 2003 in the European Alps led to higher incidence of rockfall events, probably from warm permafrost (Schiermeier, 2003, Gruber et al., 2004a). This might be indicative of the aforementioned permafrost sensitivity. At the same time, human settlements, infrastructural development and tourism in high-mountain areas such as the Alps are expanding, which intensifies the permafrost-related hazard potential.
In order to simulate the distribution and evolution of permafrost in topographically complex high-mountain areas, the process-based model TEBAL (Topography and Energy Balance) has been developed (Stocker-Mittaz et al., 2002, Gruber et al., 2004b). TEBAL simulates the energy fluxes between the atmosphere and the ground surface based on daily meteorological input data. It is well-suited for modelling the impact of climate change on mountain permafrost (Stocker-Mittaz et al., 2002). However, to date, alpine energy balance models such as TEBAL have only been driven with past or current climate data sets. Scenario simulations have been carried out only in the form of ad hoc scenarios with a very general use of climate model output (Stocker-Mittaz et al., 2002). The use of scenario time series from climate model output has been neglected so far for alpine permafrost modelling. Nevertheless, General Circulation Models (GCMs) have been used for impact studies of lowland permafrost (Anisimov et al., 1997, Stendel and Christensen, 2002). However, the horizontal resolution of a GCM (in the order of 300 km) is not able to describe explicitly the spatial distribution of the climate variables for a local site in areas of complex topography such as the Alps. Therefore, the technique of regional climate modelling (RCM) is required in such regions (Christensen et al., 1998, Giorgi et al., 2001, Frei et al., 2003, Vidale et al., 2003). This technique uses output from GCMs or re-analysis data (global analysis of the state of the atmosphere such as ERA-40 (Kallberg et al., 2004); Re-Analysis from the European Centre for Medium-Range Weather Forecasts (ECMWF)) to provide initial conditions and time-dependent lateral meteorological boundary conditions to drive high-resolution RCM simulations for selected time-slices of the global model run (e.g. Dickinson et al., 1989, Giorgi, 1990, Giorgi and Mearns, 1991). Giorgi et al. (2001) and Denis et al. (2002) showed that the simulation of the spatial patterns of precipitation and temperature over complex terrain is generally improved with the increasing resolution obtained using such regionalisation techniques. The added value of RCMs is also particularly evident for precipitation in the Alps (Frei et al., 2006).
In order to deal with the impact of changing atmospheric conditions on alpine permafrost and to assess the potential of permafrost related hazards, it is essential to establish a link between the latest developments in cryospheric and atmospheric science. Studies dealing with the use of regional climate models to drive impact models have already been carried out in other scientific disciplines, mainly in hydrology (e.g. Arnell et al., 2003, Wood et al., 2004, Kleinn et al., 2005) and agriculture science (e.g. Mearns et al., 1999, Mearns et al., 2001). A problem that occurs primarily when driving an impact model with climate model output is the spatial scale mismatch between the two model types (RCM 50 km, alpine permafrost model 25 m). However, the use of RCM output in topographically complex high-mountain environments presents additional challenges. These include:
- (1)
the low vertical resolution of an RCM that cannot represent high-mountain ranges adequately;
- (2)
the horizontal shifts of precipitation pattern (at grid boxes scale) that are observed along mountain ranges (Kleinn, 2002);
- (3)
the high spatial variability of the climate variables, and
- (4)
the reduced availability of observation data in remote mountain areas.
An additional problem from an impact modeller's point of view is the technical handling of climate model output data (data format, rotated grids, etc.), a topic not discussed in this paper.
This study aims at investigating the possibilities and limitations of the application of RCM output for local high-mountain permafrost scenario simulations, and presents two possible approaches which take into account the special challenges mentioned above. The approaches are applied in the Corvatsch region (Upper Engadine, Switzerland) in order to illustrate and discuss their potential, rather than to make an assessment of the potential future changes in the permafrost occurrence for this region.
The RCM Climate High Resolution Model (CHRM), the permafrost model TEBAL (Topographical Energy Balance), the observation data and the study site are presented in Section 2 of this paper. Section 3 introduces the two approaches. The example of the application at the Corvatsch test site is given in Section 4, followed by a discussion in Section 5, and conclusions and perspectives in Section 6.
Section snippets
Climate High Resolution Model (CHRM)
The CHRM limited area model developed at the Institute for Atmospheric and Climate Science, ETH Zurich (IAC-ETHZ), derives from the former numerical weather prediction model, HRM, of the German and Swiss meteorological service (Majewski, 1991). The HRM model has been modified by Lüthi et al. (1996) and Vidale et al. (2003) to provide an RCM. The computational grid of the model is a regular latitude/longitude grid with a rotated pole, a spatial resolution of 0.5° (about 56 km) and 20 vertical
Factors to consider
Currently, the horizontal resolution of a multi-decadal RCM simulation, as must be used for climate change studies, is limited to about 1/6° to 1/2° (approx. 20–50 km), due to limited current computational resources (e.g. Räisänen et al., 2004). However, the spatial resolution required to obtain information about alpine permafrost is a few decametres (25 m with the DHM25 digital terrain model). This is necessary, since elevation, slope and aspect change within very short distances in the
A first example of an application for the Corvatsch regions (eastern Swiss Alps)
In order to illustrate the proposed approaches, we provide in the following an application intended as a first example for the test region Corvatsch in the Swiss Alps (see Fig. 1).
Discussion
In this paper we have introduced two strategies that enable the use of output from regional climate models over topographically complex high-mountain environments.
Of the two approaches proposed, the delta approach is the simpler and faster one. It can include only a quantitative change (e.g. increase of temperature) but not a qualitative one (e.g. increase of variability). If a change in the variability ought to be considered the bias approach must be applied. Nevertheless, the calculation of a
Conclusion and perspectives
Impact modelling by using output from climate models is an interdisciplinary research field full of promise. Due to the high complexity of climate models and the specialized knowledge needed to handle these data, good collaboration between impact modellers and climate modellers is of critical importance.
As discussed, the amount of information gained from the application of one single RCM run to one single impact model is minimal. Many inherent uncertainties and errors of the models and
Acknowledgements
This study was made possible thanks to the European Cooperation in the field of Scientific and Technical Research (COST-Action 719). We are deeply grateful to Christoph Schär for allowing access to CHRM output, and for a very fruitful and friendly collaboration. Further thanks are extended to Stephan Gruber who allowed us to use TEBAL, and to Frank Paul and Wilfried Haeberli for their useful comments. We gratefully acknowledge the constructive remarks of the two reviewers (Ch. Hauck, and
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Now: Federal Office of Meteorology and Climatology, Zurich, Switzerland.
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