Affiliation:
1. Lomonosov Moscow State University, Moscow
Abstract
Te paper presents the results of studies aimed at investigation of the spatial and temporal variability of snow coverstructure on the basis of strength values and its variations obtained by means of the high-resolution penetrometer SnowMicroPen. Te possibilities of fast and independent from the observer identifcation of layers (including identifcation of weakened, potentially avalanche-dangerous layers) were estimated under the climatic conditions of Moscow and the Khibiny mountains. Horizontal areas with homogeneous underlying surface and vegetation were selected for the stratigraphic studies that made it possible to avoid a possible influence of slope relief and exposure from the obtained data on the spatial and temporal variability of the snow depth structure. Te analysis of the information obtained in winter seasons 2014/15 and 2016/17 allowed constructing detailed schemes of the snow cover evolution at the Moscow site as well as assessing the inter-annual and intra-seasonal variability of its structure. Afer the SnowMicroPen data were recorded in the course of the feld works carried out in winter 2015/16 on the Khibiny educational and scientifc base of the Lomonosov Moscow State University (city of Kirovsk), the 10-meter trench on the same profle was described in details, and direct data on the snow cover structure were obtained. Te strength values resulted from the above studies characterize the layers composed of crystals of various shapes and sizes, and they are considered as the frst step to methodology of operational defnition of the spatially-inhomogeneous stratigraphy and stability of snowpack without snowpit observations. Te data analysis showed high spatial and temporal variability of the structure and properties of snow cover even at a homogeneous area, usually described by a single snowpit.
Publisher
The Russian Academy of Sciences
Subject
Earth-Surface Processes,Geochemistry and Petrology,Water Science and Technology,Global and Planetary Change
Reference42 articles.
1. Fierz Ch., Armstrong R.L., Durand Y., Etchevers P., Greene E., McClung D.M., Nishimura K., Satyawali P.K., Sokratov S.A. The international classification for seasonal snow on the ground (UNESCO, IHP–VII, Technical Documents in Hydrology, No 83; IACS contribution No 1). Paris: UNESCO/Division of Water Sciences, 2009: viii+80 p .
2. Pirazzini R., Leppänen L., Picard G., Lopez-Moreno J.I., Marty C., Macelloni G., Kontu A., von Lerber A., Tanis C.M., Schneebeli M., de Rosnay P., Arslan A.N. European in-situ snow measurements: Practices and purposes Sensors. 2018, 18 (7): 2016. doi: 10.3390/s18072016.
3. Durand Y., Giraud G., Brun E., Mérindol L., Martin E. A computer-based system simulating snowpack structures as a tool for regional avalanche forecasting Journ. of Glaciology. 1999, 45 (151): 469–484. doi: 10.1017/S0022143000001337.
4. Hirashima H., Nishimura K., Yamaguchi S., Sato A., Lehning M. Avalanche forecasting in a heavy snowfall area using the snowpack model. Cold Regions Science and Technology. 2008, 51 (2–3): 191–203. doi:10.1016/j.coldregions.2007.05.013.
5. Schirmer M., Lehning M., Schweizer J. Statistical forecasting of regional avalanche danger using simulated snow-cover data. Journ. of Glaciology. 2009, 55 (193): 761–768. doi: 10.3189/002214309790152429.
Cited by
4 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献