Abstract
Abstract. Numerical simulations of land surface processes are important in order to perform landscape-scale assessments of earth systems. This task is problematic in complex terrain due to (i) high-resolution grids required to capture strong lateral variability, and (ii) lack of meteorological forcing data where they are required. In this study we test a topography and climate processor, which is designed for use with large-area land surface simulation, in complex and remote terrain. The scheme is driven entirely by globally available data sets. We simulate air temperature, ground surface temperature and snow depth and test the model with a large network of measurements in the Swiss Alps. We obtain root-mean-squared error (RMSE) values of 0.64 °C for air temperature, 0.67–1.34 °C for non-bedrock ground surface temperature, and 44.5 mm for snow depth, which is likely affected by poor input precipitation field. Due to this we trial a simple winter precipitation correction method based on melt dates of the snowpack. We present a test application of the scheme in the context of simulating mountain permafrost. The scheme produces a permafrost estimate of 2000 km2, which compares well to published estimates. We suggest that this scheme represents a useful step in application of numerical models over large areas in heterogeneous terrain.
Highlights
Numerical simulation is an increasingly important tool for assessment of the energy and mass balance at the earth’s surface for many fields of research and application (e.g. Wood et al, 2011; Barnett et al, 2005; Gruber, 2012)
Both iBUTTON and PERMOS site validation shows the ability of the scheme to capture results influenced by the fine-scale variability of the topography (Fig. 3)
Over all data sets an rootmean-squared error (RMSE) of 1.29 is obtained for MS and 1.21 for MP. These figures should be interpreted with caution as there is an implicit weighting based on available data points, which are unlikely to be representative of the distribution of underlying surfaces in the simulation domain
Summary
Numerical simulation is an increasingly important tool for assessment of the energy and mass balance at the earth’s surface for many fields of research and application (e.g. Wood et al, 2011; Barnett et al, 2005; Gruber, 2012). Landscapes that are heterogeneous in terms of e.g. topography, vegetation or redistribution of snow (e.g. Smith and Riseborough, 2002; Liston and Haehnel, 2007) provide a great challenge in this respect, as surface and subsurface conditions may vary on various, and often short, length scales, creating highly spatially differentiated surface– atmosphere interactions This poses, in particular, a challenge to large-area simulations, which can be summarised as follows: (1) high-resolution grids are required to capture surface heterogeneity, which is often numerically prohibitive over large areas, and efficient methods are required to make this task scalable; (2) there is often a lack of a representative forcing at the site or scale that it is required, in remote regions. At site scales several studies have applied numerical models to investigate the ground thermal regime at specific
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