Hervé Bellot

Back analysis of drifting-snow measurements over an instrumented mountainous site

Abstract The NEMO numerical model of drifting snow, whose general outlines are presented in this paper, is based on a physical model for saltation and turbulent diffusion. The model needs a set of input parameters including fall velocity, threshold shear velocity, shear velocity, mass concentration and roughness, which are obtained from empirical formulae and wind speed measured at a given height. To better determine the required field data in an alpine context, our experimental site, Col du Lac Blanc (2700ma.s.l.), French Alps, was first equipped with one anemometer and blowing-snow acoustic sensors, which proved not to be accurate enough for research purposes in the current state of development even though a new calibration curve was used. We therefore set up a Snow Particle Counter and we returned to the traditional, robust mechanical traps and a 10 m mast with six anemometers, two temperature sensors and a depth sensor to better determine friction velocity and aerodynamic roughness. Based on the studied drifting-snow events we conclude: (1) the proportionality of the aerodynamic roughness to the square of the friction velocity was confirmed, but with a varying proportionality ratio depending on the snowdrift event; (2) values of σsUF were relatively well approximated by empirical formulae from data originating from Antarctica, and (3) snowdrift concentration profiles obtained by Pomeroy’s semi-empirical formulae for the saltation layer coupled with a theoretical approach for the diffusion layer overestimated the concentration profiles for the studied blowing-snow event.

Present weather-sensor tests for measuring drifting snow

Abstarct In Antarctica, blowing snow accounts for a major component of the surface mass balance near the coast. Measurements of precipitation and blowing snow are scarce, and therefore collected data would allow testing of numerical models of mass flux over this region. A present weather station (PWS), Biral VPF730, was set up on the coast at Cap Prud’homme station, 5 km from Dumont d’Urville (DDU), principally to quantify precipitation. Since we expected to be able to determine blowing-snow fluxes from the PWS data, we tested this device first on our experimental site, the Lac Blanc pass. An empirical calibration was made with a snow particle counter. Although the physics of the phenomenon was not well captured, the flux outputs were better than those from FlowCapts. The first data from Antarctica were reanalyzed. The new calibration seems to be accurate for estimating the high blowing-snow flux with an interrogation of the precipitation effects.

Experimental study of dense snow avalanches: velocity profiles in steady and fully developed flows

Abstract In order to study channelled snow flows over rough surfaces, a laboratory-scale experiment was installed at the “Col du Lac Blanc”, a 2800 m high pass in the French Alps, near the Alpe d’Huez ski resort. It consists of a 0.2 mwide, 10 m long channel fed with snow by a motorized hopper. Both the slope of the channel and the feeding rate of the hopper can be modified. Sensors in the channel provide measurements of the velocity profile, the flow height and the shear and normal stresses at the bottom of the flow. Velocity profiles for different slopes are presented in this paper. Results indicate the presence of a highly active layer at the bottom. This layer is mainly responsible for the avalanche velocity, while the upper layer has a much smaller velocity gradient. A first interpretation of both layers is given.

Evaluation of the FlowCapt Acoustic Sensor for the Aeolian Transport of Snow

FlowCapt acoustic sensors, designed for measuring the aeolian transport of snow fluxes, are compared to the snow particle counter S7optical sensor, considered herein as the reference. They were compared in the French Alps at the Lac Blanc Pass, where a bench test for the aeolian transport of snow was set up. The two existing generations of FlowCapt are compared. Both seem to be good detectors for the aeolian transport of snow, especially for transport events with a flux above 1 g m 22 s 21. The second-generation FlowCapt is also compared in terms of quantification. The aeolian snow mass fluxes and snow quantity transported recorded by the second-generation FlowCapt are close to the integrative snow particle counter S7 fluxes for an event without precipitation , but they are underestimated when an event with precipitation is considered. When the winter season is considered, for integrative snow particle counter S7 fluxes above 20 g m 22 s 21 , the second-generation FlowCapt fluxes are underestimated, regardless of precipitation. In conclusion, both generations of FlowCapt can be used as a drifting snow detector and the second generation can record an underestimation of the quantity of snow transported at one location: over the winter season, the quantity of snow transported recorded by the SPC is between 4 and 6 times greater than the quantity recorded by the second-generation FlowCapt.

Wind and drifting-snow gust factor in an Alpine context

Abstarct Wind-transported snow is a common phenomenon in cold windy areas, creating snowdrifts and contributing significantly to the loading of avalanche release areas. It is therefore necessary to take into account snowdrift formation both in terms of predicting and controlling drift patterns. Particularly in an Alpine context, drifting snow is a nonstationary phenomenon, which has not been taken into account in physical modeling carried out in wind tunnels or in numerical simulations. Only a few studies have been conducted to address the relation between wind gusts and drifting-snow gusts. Consequently, the present study was conducted at the Lac Blanc pass (2700ma.s.l.) experimental site in the French Alps using a snow particle counter and a cup anemometer in order to investigate drifting-snow gusts. First, it was shown that the behavior of the wind gust factor was coherent with previous studies. Then the definition of wind gust factor was extended to a drifting-snow gust factor. Sporadic drifting-snow events were removed from the analysis to avoid artificially high drifting-snow gust factors. Two trends were identified: (1) A high 1 s peak and a mean 10 min drifting-snow gust factor, greater than expected, were observed for events that exhibited a gamma distribution on the particle width histogram. The values of drifting-snow gust factors decreased with increasing gust duration. (2) Small drifting-snow gusts (i.e. smaller than or of the same order of magnitude as wind gusts) were also observed. However, in this case, they were systematically characterized by a snow particle size distribution that differed from the two-parameter gamma probability density function.

Snow particle speeds in drifting snow

Knowledge of snow particle speeds is necessary for deepening our understanding of the internal structures of drifting snow. In this study, we utilized a snow particle counter (SPC) developed to observe snow particle size distributions and snow mass flux. Using high-frequency signals from the SPC transducer, we obtained the sizes of individual particles and their durations in the sampling area. Measurements were first conducted in the field, with more precise measurements being obtained in a boundary layer established in a cold wind tunnel. The obtained results were compared with the results of a numerical analysis. Data on snow particle speeds, vertical velocity profiles, and their dependence on wind speed obtained in the field and in the wind tunnel experiments were in good agreement: both snow particle speed and wind speed increased with height, and the former was always 1 to 2 m s−1 less than the latter below a height of 1 m. Thus, we succeeded in obtaining snow particle speeds in drifting snow, as well as revealing the dependence of particle speed on both grain size and wind speed. The results were verified by similar trends observed using random flight simulations. However, the difference between the particle speed and the wind speed in the simulations was much greater than that observed under real conditions. Snow transport by wind is an aeolian process. Thus, the findings presented here should be also applicable to other geophysical processes relating to the aeolian transport of particles, such as blown sand and soil.

Size of snow particles in a powder-snow avalanche

Little quantitative information is available concerning the size of ice particles in the turbulent clouds of powder-snow avalanches. To quantify particle size distributions, we have developed an experimental device that collects particles in real-scale powder avalanches. The device was placed on the concrete bunker of the Swiss Vallee de la Sionne avalanche dynamics test site. On 31 January 2003, a large powder-snow avalanche struck the bunker and we were able to collect particle samples. The collected particles have been photographed and the pictures digitized. An image analysis tool allows us to determine an equivalent particle radius. The captured particles have a geometric mean of 0.16 mm; the largest particles were 0.8 mm in size and the smallest particles 0.03 mm.

Monitoring Debris Flow Propagation in Steep Erodible Channels

Debris flows mobilize high sediment loads especially during intense rainfall events. The volume of these surges is known to dramatically grow during propagation by scouring of the unconsolidated sediment stored in the channel before the event. The current prediction tools used by engineers to manage debris flow hazards are mostly based on empirical relationships with a high level of uncertainty. This situation arises in particular because of our insufficient understanding of interactions between the flow and the erodible bed of the torrent. In order to address this issue, field monitoring stations were deployed in 2010 in the Manival and the Real Torrents, two very active sites in the French Alps. Several stations were installed in different locations along the same torrent to investigate the spatial variability of the measured parameters. Each station was equipped with rain gauges, flow stage sensors, set of geophones and camera. The collected information allows developing a data base including the rainfall duration-intensity-volume, the flow depth, the front velocity and the surge volume. The objective is to characterize the changing nature of the debris-flow properties along the torrents and then to analyse the effect of channel conditions on debris-flow scouring.

A meteorological and blowing snow dataset (2000–2016) from a high-altitude alpine site (Col du Lac Blanc, France, 2720 m a.s.l.)

A meteorological and blowing snow dataset issued from the high-altitude experimental site of Col du Lac Blanc (2720 m altitude, Grandes Rousses mountain range, France) is presented and detailed in this paper. Emphasis is placed on data 15 relevant to the observations and modelling of wind-induced snow transport in alpine terrain. This process strongly influences the spatial distribution of snow cover in mountainous terrain with consequences for snowpack, hydrological and avalanche hazard forecasting. In-situ data consist of wind (speed and direction), snow depth, and air temperature measurements (recorded at four automatic weather stations), a database of blowing snow occurrence and measurements of blowing snow fluxes obtained from a vertical profile of Snow Particle Counters. Observations data span the period from December 1 st to 20 March 31 st for each winter season from 2000-2001 until 2015-2016. The time resolution varies from 15 min. at the beginning of the period to 10 min. for the last years. Atmospheric data from a local meteorological reanalysis (SAFRAN) are also provided from 1 August 2000 to 1 August 2016. A Digital Elevation Model (DEM) of the study area (1,5 km2) at 20-cm resolution is also provided in RGF 93 Lambert 93 coordinates This dataset has been used in the past to develop and evaluate physical parameterizations and numerical models of blowing and drifting snow in alpine terrain. Col du Lac Blanc is also a 25 target site to evaluate meteorological and climate models in alpine terrain. It belongs to the Cryobs-Clim observatory (the CRYosphere, an OBServatory of the CLIMate) which is a part of the national research infrastructure OZCAR (Critical Zone Observatories – Application and Research) (Gaillardet et al., 2018). The data are placed on the repository of the OSUG datacenter doi:10.17178/CRYOBSCLIM.CLB.all . Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2018-74 O pe n A cc es s Earth System Science Data D icu ssio n s Manuscript under review for journal Earth Syst. Sci. Data Discussion started: 25 June 2018 c