000170100 001__ 170100 000170100 005__ 20180317095109.0 000170100 0247_ $$2doi$$a10.5194/tc-5-893-2011 000170100 022__ $$a1994-0440 000170100 02470 $$2ISI$$a000298494200006 000170100 037__ $$aARTICLE 000170100 245__ $$aSpatio-temporal measurements and analysis of snow depth in a rock face 000170100 260__ $$c2011 000170100 269__ $$a2011 000170100 336__ $$aJournal Articles 000170100 520__ $$aSnow in rock faces plays a key role in the alpine environment for permafrost distribution, snow water storage or runoff in spring. However, a detailed assessment of snow depths in steep rock walls has never been attempted. To understand snow distribution in rock faces a high-resolution terrestrial laser scanner (TLS), including a digital camera, was used to obtain interpolated snow depth (HS) data with a grid resolution of one metre. The mean HS, the snow covered area and their evolution in the rock face were compared to a neighbouring smoother catchment and a flat field station at similar elevation. Further we analyzed the patterns of HS distribution in the rock face after different weather periods and investigated the main factors contributing to those distributions. In a first step we could show that with TLS reliable information on surface data of a steep rocky surface can be obtained. In comparison to the flatter sites in the vicinity, mean HS in the rock face was lower during the entire winter, but trends of snow depth changes were similar. We observed repeating accumulation and ablation patterns in the rock face, while maximum snow depth loss always occurred at those places with maximum snow depth gain. Further analysis of the main factors contributing to the snow depth distribution in the rock face revealed terrain-wind-interaction processes to be dominant. Processes related to slope angle seem to play a role, but no simple relationship between slope angle and snow depth was found. Further analyses should involve measurements in rock faces with other characteristics and higher temporal resolutions to be able to distinguish individual processes better. Additionally, the relation of spatial and temporal distribution of snow depth to terrain – wind interactions should be tested. 000170100 6531_ $$aSpatial-Distribution 000170100 6531_ $$aMountain Catchment 000170100 6531_ $$aTerrain 000170100 6531_ $$aTransport 000170100 6531_ $$aCover 000170100 6531_ $$aVariability 000170100 6531_ $$aLandscape 000170100 6531_ $$aModel 000170100 6531_ $$aLidar 000170100 6531_ $$aMass 000170100 700__ $$aWirz, V. 000170100 700__ $$aSchirmer, M. 000170100 700__ $$aGruber, S. 000170100 700__ $$0245914$$aLehning, M.$$g167659 000170100 773__ $$j5$$q893-905$$tThe Cryosphere Discussions 000170100 909CO $$ooai:infoscience.tind.io:170100$$pENAC$$particle 000170100 909C0 $$0252326$$pCRYOS$$xU12533 000170100 917Z8 $$x173008 000170100 937__ $$aEPFL-ARTICLE-170100 000170100 973__ $$aEPFL$$rREVIEWED$$sPUBLISHED 000170100 980__ $$aARTICLE