J.L. Michaux 1, F. Naaim-Bouvet\ M. Naaim\ G. Guyomarc'h 2

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$THE ACOUTIC NOWDRIFT ENOR: INTERET, CALIBRATION AND REULT J.L. Michaux 1, F. Naaim-Buvet\ M. Naaim\ G.$

1 THE ACOUTIC NOWDRIFT ENOR: INTERET, CALIBRATION AND REULT J.L. Michaux 1, F. Naaim-Buvet\ M. Naaim\ G. Guymarc'h 2 1 : Cemagref, nw avalanche engineering and trrent cntrl research unit, Grenble, France 2 : Mete France, CEN (nw tudy Center), Grenble, France ABTRACT: During a drifting snw event, it seems t be imprtant t knw the flux f blwing snw. Indeed, the height f the snw accumulatin in an avalanche departure zne and als snwdrift n rads depend n this quantity. In rder t estimate this flux, we have develped at Cemagref, in cllabratin with Hydremac, an acustic snwdrift sensr. It is made f a micrphne lcated in an aluminum ple. The ple is expsed t the snw particle flux and the sund prduced by the particle impacts is recrded as an electrical signal. Hwever, this signal depends nt nly n the particles flux, but als n the type 01 particles, the presence f a snwfall r nt, the wind nise n the sensr, etc. Therefre we have dne experiences, bth in situ n ur experimental site f high altitude called Cl du Lac Blanc, and in a climatic wind tunnel (CTB, France), in rder t calibrate ur sensr i.e. t establish a relatin between the signal n the sensr, and the flux f particles. Mrever, thank t this sensr, we btained infrmatin cncerning the threshld velcities f ersin and depsit, and relatins between wind and drifting snw. This paper presents ur results. KEYWORD: Drifting snw - snwdrift acustic sensr _. flux threshld velcities 1. INTRODUCTION Cemagref's Etna divisin and Cen f Mete France have been wrking tgether n drifting snw fr ten years At the present time, we are develping an acustic snwdrift sensr, which aims at measuring the flux f drifting snw. Indeed, the flux f drifting snw is an input required by ur mdel f snwdrift (Naaim and thers, 1998). We are calibrating this sensr, which is sensitive t the flux, but als t parameters such as the wind r the type f snw particles. Therefre, we need t determine the effect f each parameter, in rder t gauge the sensr. T this purpse, we have realized experiments, bth in situ, n ur experimental site f high altitude, at Lac Blanc Pass, near the ski resrt f Alpe d'huez (France), and in a climatic wind tunnel at CTB (Nantes, France). This paper presents the first steps f the calibratin, which were realized this year, and the present use f this acustic snwdrift sensr. 2. CALIBRATION OF THE ACOUTIC NOWDRIFT ENOR 2.1. Technical aspect f tne sensr Cemagref's Etna unit has develped an acustic snwdrift sensr (Fig. 1.), in cllabratin with Hydremac (Fnt and thers, 1998). It is basically a miniature micrphne lcated at the base fa 2 m lng aluminum ple. The ple is expsed t the snw particle flux, and during snwdrift, part f the flux impacts n the ple. The sund prduced by these impacts is recrded as an electrical signal. The lwerfrequency signal prduced by the wind and the higher-frequency signal, utside f the audible range, are filtered ut. The recrded utput vltage indicates when snwdrift ccurs. Crrespnding authr address: Michaux J.L. Cemagref, nw avalanche engineering and trrent cntrl research unit Dmaine Universitaire, 2 rue de la Papeterie, BP 76, aint-martin-d'heres cedex, France. Tel: Fax: lean-luc.michaux@grenble.cemagref.fr Figure 1: The acustic snwdrift sensr. 390

2.2 Experiments in the climatic wind tunnel f CTB Descriptin f experiments In rder t gauge the acustic snwdrift sensr, we have realized ten days f experiments in the climatic wind tunnel f CTB

2 2.2 Experiments in the climatic wind tunnel f CTB Descriptin f experiments In rder t gauge the acustic snwdrift sensr, we have realized ten days f experiments in the climatic wind tunnel f CTB (Nantes, France), n the framewrk f an Eurpean prject. This wind tunnel f 26 m length, 10m width and 7 m high, allws t wrk with extreme cnditins such as temperature f -15 C, regular r gust winds up t 25 m.s-1; and als t prduce artificial snw, thanks t snw guns (Fig. 2). The advantage f this wind tunnel is t permit the realizatin f many experiments in a shrt time,. with well-cntrlled parameters. - A wind lwer than 11.4 m.s-1 des nt create significant signal n the sensr - Fr a wind speed higher than 11.4 m.s-1, the wind signal can be taken as a linear functin f the wind speed, in a first apprximatin: wind = 15*Vwind -121 (R 2 =0.7), (1) - where wind is the signal prduced by the wind and Vwind is the wind velcity. This law is wrking with errrs frm 20% t 80% n the signal value due t the wind, depending n the wind speed. These errrs seem t be imprtant, hwever they keep small relatively t the signal during a drifting snw episde. Wind nise n the drifting snw acustic sensr '> implified gauging law y =15,215x-121,31 t~::===~r2===0,=69=53=======~===~=== }ljuf------~."l_-.~---.: r~+-i---l~_-- '_'_-_i'~'_.-~-~---i en Wind speed (m.&-i) ~Nise n the sensr fr winds> lom.s-l. Nise n the sensr fr winds < 10 m.s-l _ Linear Figure 2 : the wind tunnel f CTB. Wind nise n the sensr A part f experiments realized in the wind tunnel f CTB was devted t the determinatin f the wind signal n the acustic snwdrift sensr. T this purpse, we have first realized tw types f experiments withut snw: The first ne cnsisted in increasing regularly the wind speed in the wind tunnel, frm 3 t 23 m.s 1, and at the same time t recrd the signal n 6 acustic snwdrift sensrs, fixed in the wind tunnel. The secnd experiment was similar, except that the wind was blwing by gusts, and nt regularly. Gusts had an average wind speed f 10 m.s-1, then 20 m.s-1, and an amplitude f 2.5 m.s-1 The first step f the data prcessing was the e!imi~atin f the wind tunnel nise (fans, vibratins and mtrs) n the data. T this purpse, we smthed data, averaging their n 1 minute, whereas the initial recrding was every secnd. The tw experiments prduced similar results (Fig. 3): Figure 3: Wind n,se n the acustic snwdrift sensr, Relatin between signal and flux: The mass flux f drifting snw is ne parameter in ur numerical mdel. Up t nw, the mass flux has been inferred frm the wind speed by means f an empirical law (Pmery and Gray, 1990). Hwever, t imprve the mdel, we wuld like t btain measurements f the flux, in rder t take int accunt snwfalls. Therefre, we plan t calibrate the acustic sensr, in rder t deduce the flux f drifting snw frm the recrded signal. Therefre, we have realised experiments in the CTB wind tunnel in which we cmpared the average mass flux during ne experiment, and the average recrded signal. The mass flux was determined using mechanical snw traps. These snw traps, called "butterfly nets", have a rectangular metal frame (15 cm* 2 cm) with an attached nyln bag. The traps, facing the prevailing wind directin, have been fixed at different heights n a ple, next t the acustic sensr (Fig. 2). We btain the drifting snw flux by integrating the mass weight at each height. These values f flux were cmpared with the average signal n the snwdrift acustic sensr, fr each experiment, with regular winds r gusts. 391

These firsts results seem t be interesting. The signal n the snwdrift acustic sensr is prprtinal t the flux f drifting snw (Fig. 4). This result is a preliminary.

3 These firsts results seem t be interesting. The signal n the snwdrift acustic sensr is prprtinal t the flux f drifting snw (Fig. 4). This result is a preliminary. It was dne with a given type f snw (artificial snw) in the cld wind tunnel f CTB. Furthermre, studies have shwn that the signal depends n the type f snw which hit the ple (see 2.3.) Therefre, fr the future, we wuld like t btain a gauging which links a given signal with a flux, fr a given meterlgical event (temperature, snw type, etc.). This sensr will be cupled with the mdel CROCU f Mete France (Brun and thers, 1992), which simulates the snw type in the snw mantle.. ensr 2 ensr 3 ensr4.. ensr 5 ensr 6 linear lendancy Flw (kg. linear m-1.h-1) Figure 4: relatin between flw and signal n the acustic snwdrift sensr. Preliminary results fr experiments in the wind tunnel f CTB Experiments in situ, at Cl du Lac Blanc Descriptin f the experimental site In rder t fllw the three-dimensinal spatial distributin f snw during the winter and t determine where snw accumulates and settles fr a given meterlgical event, we set up tw netwrks f metallic snw ples at Lac Blanc Pass (Guymarc'h and thers., 2000). The prevailing winds at Cl du Lac Blanc are frm the Nrth r uth. The high wind speeds and the snw cver are favurable t drifting snw. On this site, a square f 20 ples and a 200 m lng prfile f height ples have been set up (This area is bth an ersin zne (near the pass) as well as an accumulatin zne (Michaux and thers, 2000). We climbed t this experimental site at least nce a week, depending n snwdrift event frecasts, in rder t measure the snw depth at each snw ple. In additin, a stratigraphic prfile f the snwpack and a ram test were carried ut t cllect data n the time prgressin f the snwpack and the depth f the snw. Autmatically recrded meterlgical data cmplete these measurements. A data lgger recrded the fllwing parameters every 15 minutes (with a scan rate f 1 secnd): average, maximum and minimum wind speed, directin, precipitatin, and temperature. Anther weather statin situated nearby has equipped with an ultrasnic sensr measures the snw depth. Nevertheless, all these meterlgical data nt sufficient t test the numerical model' snw mass flux and the threshld velcity als necessary fr these calculatins. Fr iii reasn six acustic sensrs were installed ~ a 20D-m prfile. These sensrs are lcated in" ersin area, in the transprt zne and in lile depsitin zne. Variatin f the signal with the type f snw The fllwing graph (Fig.5) illustrates the signra recrded by the acustic snwdrift sensr, (average signal ver 15 minutes versus the wqi velcity) fr varius snwdrift episdes at CId1 Lac Blanc and thus fr different snw types." rder t determine the snw type, we decided, rely n the AFRAN (Durand and thers, 1993). CROCU (Brun and thers, 1992) mdel, fr_ reasns. Firstly, we were nt always n experimental site at the beginning f the driflilt snw event and thus we have n ther infrmatin abut the snw type. ecndly.. are develping a cnnected mdel in which the utput f AFRAN-CROCU is ging t be the input f ur numerical drifting snw mdel NEMO (Naaim-Buvet and thers, 2000). On March 4, 1998, we bserved an episde wi bth snwfall and wind that appears as wideir scattered data pints in Figure 5. In this case. the mass flux was crrelated bth with the will speed and the snwfall intensity, which was Id cnstant. This scattering f data was always bserved in episdes f snwdrift with snwfal during the winter. The signal induced by runded grains was higher than the ne generated by new snw. faceted grains (Fig. 5) Hwever, we shuld keep in mind that this difference in signal might be caused by a shift f the signal due t til variatin f the snw depth arund the sel1lf during the mnth f March. Fig. 6. shw" evlutin in time ft the snw depth at sensr' 5; the increase during March is caused IIf snwfall events withut wind. The differerll8 between signals fr varius types f grain~~ smaller fr anther sensr where the snw ljqii" variatin was less (Fig. 7). These bservatioll cnfirm that a snw depth sensr must be a_ t the acustic sensr in an peratinal use. '": will allw a crrectin f the data with regard the ideal situatin n which the sensr '" calibrated (ersin area withut snw). 392

1800 _ 1600 +---------Y=-'-:'~'!L-_btJ~-+_ 0,,-.083,..,...;"'''''''''' =e 1400 -I-----~== =0.966 -; 1200-l--------il gt 1000 +----'1-E-"""""""----ili'*~; jl7--...; ~ 800 +----'-'--=-""~~.~.,"-----...;.> "5 800 -I-----~ g.

4 1800 _ Y=-'-:'~'!L-_btJ~-+_ 0,,-.083,..,...;"'''''''''' =e I-----~== = ; 1200-l il gt '1-E-"""""""----ili'*~; jl7--...; ~ '-'--=-""~~.~.," ;.> " I-----~ g I---.-a-~.,J< < I----~ ~~~M ~= c~,... -_, ----i Wind speed (ms' 1 ) 0 03/03/99: faceted grains.01/16/99 t 01/18/99 : faceted grains /99 : new snw.03/04/99 : with snw fall x 03/17/99 t 03/20/99: runded grains Figure 5: Vltage (mean value ver 15 min) frm acustic sensr n. 5 versus wind speed (mean value ver 15 min) fr different drifting-snw events _ " _. E ~1 ~ 0.8 ~ 0.6 _-~ fl.---.;. 0c:: 0.4 j \, d III Or} ~:.:s= -.,...--_- -Z~7-:-----c, 13/11/ /99 27/ / Date Figure 6: Evlutin f snw depth near acustic sensr no.5 during the winter f :> 1400 E '; 1200 C>.!! > 800 Q, Wind speed (m.s ') I Frm (2h30) (24 h) x Frm (2h15) t 20/03199 (2Ih45) Figure 7: Vltage (mean value ver 15 min) frm acustic sensr no.1 versus wind speed (mean value ver 15 min) 3. FIRT REULT 3.1. Determinatin f drifting snw perids This acustic snwdrift sensr is fr the mment peratinal as a detectr f snwdrift episdes. It indicates when snwdrift ccurs, and values n the signal give infrmatin abut the intensity f the drifting snw episde. In figure 8, we present an example f the signal bserved n the sensr, during a drifting snw event. Figure 9 shws the results f ne year f drifting snw n ur experimental site f Cl du Lac Blanc; the sensr detected these episdes. This use f the acustic snwdrift sensr permitted us t create a database f snwdrift events n ur experimental site, with many parameters (snw depth, wind speed, temperature, etc.) (Guymarc'h and thers, 2000). This data base will be use in rder t perfrm ur numerical mdel f drifting snw ", 20.j------t~- f =f 2500 ~ =~ i 15 ~ 1500 g.e 10 '5 ~ 1000 ~ / / / Date 1-Wind speed- Vltage t Figure 8: Wind speed and drifting snw frm January 26 t F.ebruary 1. '00% 90%,/' 80% ~70% ~60% I~ 40% t/. 30%,: 20% ii, 10% /" 'f. O%.JL--=::.,...-==.;.:..-==...--==., 01/ /99 Date f02000 mv<yalues<3qoo mv : mv<values<2000 mv a 500 mvc:.values<l000 mv 0200 mvc:.values<500 mv G 100 mv<values<200 mv 050 mv<values<100 mv C Wi1hu1 drifting-snw EJ Withut data Figure 9: Occurrence f drifting-snw events Hysteresis phenmenn' fr threshld velcities This sensr is an imprtant tl, nt nly fr engineering and detectin f drifting snw episdes, but als fr research n drifting snw. Fr example, it allwed us t highlight the phenmenn f hysteresis f threshld velcities fr ersin and depsit. Indeed, we bserved during experiments in the climatic wind tunnel f CTB, that the signal n the sensr fr a given wind speed is lwer during the increasing phase f the event, than during the decreasing phase. The threshld velcity f ersin (which is the minimum wind speed fr which there is ersin f snw) is higher than the threshld velcity f 393

depsit (threshld wind speed belw which there 3000 is depsit) (Fig.1 0).. 1--- - - - - - --I _ 2500 +---!-..-----t-----_--.! Threshldvelcity : Hysteresis phenmenn 15 ------ --------------..------~-l ~.

5 depsit (threshld wind speed belw which there 3000 is depsit) (Fig.1 0) I _ ! t-----_--.! Threshldvelcity : Hysteresis phenmenn ~-l ~......~_. - '..."1 '.i, i I0'..- I 1 i.. I- Wind increasing II.; 5.,IJ.Wind decreasing ~ ~,. I! i i ignal (mv) Figure 10: Hysteresis phenmenn The snwdrift: a nn-linear phenmenn The gust factr relating t the signal f the acustic snwdrift sensr, defined as the rati G s.= maximum signal f the acustic sensr / average signal, can prvide infrmatin abut the snwdrift. T this purpse, we used an acustic snwdrift sensr lcated at ur experimental site f Cl du Lac Blanc. We first remved the ffset f the sensr (50mV). Then, we filtered ut the average signal less than 5 mv, because lwer values d nt crrespnd t snwdrift. The gust factr was then calculated every 15 minutes fr the whle winter (scan rate f 1 secnd) (Michaux and thers, 2000). We calculated als!tole wind gust factrs. Thanks t these data, we highlighted tw types f drifting-snw events' - A first type f perids f weak snwdrift, - A secnd type f perids f heavy snwdrift. The first scenari (weak snwdrift) crrespnds t areas 1 and 3 in Figure 11, and areas A and B in Figure 12. In the first case (area 1 in Figure 11 and A in Figure 12), high wind gust factrs were fund, indicating highly gusty winds, but very lw average snwdrift signals and snwdrift gust factrs were bserved. Thus, this scenari des nt shw significant ersin, snwdrift, and depsitin. The secnd case (area 3 in Figure 11 and B in Figure 12) is characterised by gusty snwdrift episdes with spradic wind gusts generating mderate snwdrift. The secnd scenari (heavy snwdrift) crrespnds t zne 2 f Figure 11 and part C f Figure 12. Due t the limited utput vltage f 5000 mv fr the acustic sensr, the maximum snwdrift gust factr is 50 fr average signals greater than 100 mv, causing the cut-ff in Figure 12. This type f snwdrift ccurs during mre regular wind episdes characterised by lw wind gust factrs. 394 >-..! ~--=-----""""...::._.J_----.J Ql := ~ 1500 '0 g >.r: 1000 li '5-500 it Figure 11: The average snwdrift signal 011 acustic sensr n 5 at Cl du Lac Blanc , g :--=---'---=-,-..--_-_--_-_--l--, ~; l/l _ ,-'-----t:---;l (1) I -: ~ l--t-~.---t""'----- l~ $a ~ :~~_~---r;)--- u....l!! ' r--...~ t'..,~ \ iii 50 :::l Cl 0 Figure 12: The snwdrift gust factr recrded by acustic sensr n05 at Cl du Lac Blanc. This study f the snwdrift gust faclf demnstrates that snwdrift is mre substantial/vluminus when it is generated by I regular, sufficiently strng wind than when it appears with spradic wind gusts. This imprtalt" result will allw us t smewhat simplify thf. numerical mdel f drifting snw used Cemagref. 4. CONCLUION The calibratin f the acustic snwdrift sen is ging well. We have realized prelimin validatins cncerning the wind nise n sensr and the relatin between signal and ft thanks t experiments, bth in situ at Lac BI Pass, and in the climatic wind tunnel f csnt We highlighted the prblems that we need slve in rder t gauge the sensr, in part~ the fact that each type f snw might prduce particular signal n the acustic sensr, and a snw depth sensr must be added. At present time, the sensr can be used as detectr f drifting snw perids. We. created a database cncerning snwdrift P'G1"'-XC n ur experimental site. This data base win used in rder t perfrm ur drifting s numerical mdel. Mrever, it has yet allwed t find interesting results, cncerning thres velcities f ersin and depsit, and. cncerning the meterlgical cnditins wh can generate an imprtant event f snw

6 (regular high wind speed is mre favrable t snwdrift than high wind gusts). The next step f the calibratin will be the determinatin f the accurate link between signal and flux fr each type f snw. 5. ACKNOLEDGMENT This study required an imprtant technical supprt which was realized by Jean Michel Panel and Philippe Pugliese (electrnical team f the CEN), and Frederic Ousset (Cemagref). The ATA (afety service f f Alpe d'huez resrt) as usual, helped us n the grund. This study was partially funded by the Rhne-Alpes Regin. 6. REFERENCE Brun, E., P. David, M. udul and G. Brunt A numerical mdel t simulate snw-cver stratigraphy fr peratinal avalanche frecasting. J. Glacil., 38(128), Durand, Y., E. Brun, L. Merindl, G. Guymarc'h and E. Martin A meterlgical estimatin f the relevant parameters fr snw mdels. Ann. Glacil., 18, Fnt, D., F. Naaim-Buvet and M. Russel Drifting snw acustic detectr: experimental tests in La Mlina, panish Pyrenees. Ann. Glacil., 26, Guymarc'h G., Y. Durand, L. Merindl, F. Naaim Buvet, Climatlgy f an experimental muntainus lcatin fr studies n snwdrift. Prceedings, Internatinal nw science Wrkshp, Octber 2000, Big sky Mntana, in press. Michaux, J-L., F. Naaim-Buvet, and M. Naaim Transprt de la neige par Ie vent sur un site de mntagne : mesures et mdelisatin numerique a I'echelle du culir. La Huille Blanche,, Michaux J.L., F. Naaim-Buvet, and M. Naaim Drifting snw studies ver an instrumented muntainus site. Part II: Measurements and numerical mdel at small scale, in press, Ann. Glacil. Naaim, M., F. Naaim-Buvet and H. Martinez Numerical simulatin f drifting snw: ersin and depsitin mdels. Ann. Glacil., 26, Naaim-Buvet. F., Y. Durand, M. Naaim, G. Guymarc'h, J.L. MichauX' L. Merindl, Numerical experiments f wind transprt ver a muntainus instrumented site, at small, medium, and large scale. Prceedings, Internatinal nw science Wrkshp, Octber 2000, Big sky Mntana, in press. Pmery, J.W. and D.M. Gray altatin f nw. Water Resr. Res, 26(7),

Operational Use of the Model Crocus

Operational Use of the Model Crocus Operatinal Use f the Mdel Crcus by French Avalanche Frecast Services E.Brun Meterlgie Natinale Centre d'etudes de la Neige BP 44 Dmaine Universitaire 3842 St-Martin d 'eres France ntrductin Since 1971