Abstract. Terrain parameters like topographic horizon and sky view factor (SVF) are used in numerous fields and applications. In atmospheric and climate modelling, such parameters are utilised to parameterise the effect of terrain geometry on radiation exchanges between the surface and the atmosphere. Ideally, these parameters are derived from a high-resolution digital elevation model (DEM) because inferring them from coarser elevation data induces a smoothing effect. Computing topographic horizon with conventional algorithms, however, is slow because large amounts of non-local terrain data have to be processed. We propose a new and more efficient method, which is based on a high-performance ray-tracing library. The new algorithm can speed up horizon calculation by 2 orders of magnitude relative to a conventional approach. By applying terrain simplification to remote topography, the ray-tracing-based algorithm can also be applied with very high-resolution (<5 m) DEM data, which would otherwise induce an excessive memory footprint. The topographic horizon algorithm is accompanied by an SVF algorithm, which was verified to work accurately for all terrain – even very steep and complex terrain. We compare the computational performance and accuracy of the new horizon algorithm with two reference methods from the literature and illustrate its benefits. Finally, we illustrate how sub-grid SVF values can be efficiently computed with the newly derived horizon algorithm for a wide range of target grid resolutions (1–25 km).

Abstract. Terrain parameters like topographic horizon and sky view factor (SVF) are used in numerous fields and applications. In atmospheric and climate modelling, such parameters are utilized to parameterise the effect of terrain geometry on radiation exchanges between the surface and the atmosphere. Ideally, these parameters are derived from a high-resolution digital elevation model (DEM), because inferring them from coarser elevation data induces a smoothing effect. Computing topographic horizon with conventional algorithms is however slow, because large amounts of non-local terrain data have to be processes. We propose a new and more efficient method, which is based on a high-performance ray tracing library. By applying terrain simplification to remote topography, this allows the application of the new algorithms also with very high-resolution (< 5 m) DEM data, which otherwise would induce an excessive memory footprint. The topographic horizon algorithm is accompanied by a SVF algorithm, which was verified to work accurately for all terrain – even very steep and complex one. We compare the computational performance and accuracy of the new horizon algorithm with two reference methods from literature and illustrate its benefits. Finally, we illustrate how sub-grid SVF values can be efficiently computed with the newly derived horizon algorithm for a wide range of target grid resolutions (1–25 km).

&lt;p&gt;In mountainous regions, incoming surface radiation is strongly influenced by surrounding and local terrain. The direct beam part of incoming shortwave radiation depends both on local slope angle and azimuth as well as on neighbouring terrain, which can induce topographic shading. Shortwave radiation can be reflected (multiple times) by terrain, which leads to enhanced incoming diffuse shortwave radiation for locations with a reduced sky view factor (SVF) &amp;#8211; particularly under snow-covered conditions when surface reflectivity is high. Finally, incoming longwave radiation can also be modulated by neighbouring terrain due to radiation exchange between facing slopes.&lt;/p&gt;&lt;p&gt;Considering these effects in spatially distributed land surface models &amp;#8211; either stand-alone or embedded in weather and climate models &amp;#8211; typically requires the following topographic quantities: slope angle, slope aspect, terrain horizon and SVF. The first two quantities can be computed rapidly because they only depend on local terrain. The computation of the latter two quantities is however expensive, particularly for high-resolution (~30 m) digital elevation models (DEMs), because a large quantity of non-local DEM information has to be processed. We developed a new efficient algorithm for terrain horizon computation, which is based on a high-performance ray-tracing library. A benchmark against conventional algorithms confirmed its high performance &amp;#8211; particularly for DEMs with very high resolution and for large terrain horizon search distances. Furthermore, due to the smooth representation of terrain by a triangle mesh, the new algorithm does not reveal artefacts in the computed horizon line in cases where the horizon is formed by proximal terrain. Finally, we demonstrate that the new algorithm is also eligible to compute sub-grid SVF for large spatial domains in a very efficient way. Sub-grid SVF is a useful quantity to parameterise above-mentioned topographic effects on surface radiation in weather and climate models applied on regional or even global scales.&lt;/p&gt;