Avalanche Forecasting- CRocusMEPRAPC SOFTWARE: A TOOL FOR LOCAL SIMULATIONS OF SNOW

COVER STRATIGRAPHY AND AVALANCHE RISKS

Gerald Giraud*, Eric Martin, Eric Brun and Jean-Pierre NavarreMeteo-France, Centre d'Etudes de la Neige

Abstract: To help the regional avalanche forecaster and to describe the great variability of the snow pack andthe avalanche risk, the CEN (Centre d'Etudes de la Neige) bas developed the SafranCrocusMepra automaticchain, which simulates snow cover stratigraphy and avalanche risks on many typical slopes representative of thedifferent French massifs.

With this tool under Unix operating system, local simulations using snow pit and meteorological dataare not easy to make. Then, a PC software has been developed in an oriented object language (Visual C++) usingonly Crocus and Mepra models. This first version of CrocusMepraPC allows us to :

~ make easily Crocus and Mepra simulations in a local mode using window interface to input the initialsnow profile and meteorological'data, run the models and visualize the results : detailed graphics ofCrocus stratigraphic and ram profile, Mepra natural and accidental risks, unstable levels., ,and graphicsofhourly snow surface temperature and water bottom runoff for the whole simulation.

~ compare easily the results of different runs in analyse or forecast mode~ have a portable and an education tool

Keywords: snow model, avalanche forecasting, computer tool

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1. Introduction

Since the 70's, different models have beendeveloped and used by various snow and avalancheresearch centres for local or regional avalancheforecasting. Statistical methods using discriminantanalysis and nearest neighbours seem to be the mostpopular approaches (Bois et aI., 1975; Buser et aI.,1987).At the same times, numerical models have reendeveloped to simulate snow cover processes(Anderson, 1976; Colbeck, 1973; Obled and Rosse,1975; Navarre, 1975). These physically-basedmodels simulate the evolution of the snow cover asa function of the weather conditions. They include arepresentation of the principal phenomena affectingthe energy and mass balance of the snow pack andalso metamorphism for a new generation (Brun etaI., 1992; Lehning et aI, 1998). The last avalancheforecasting method is based on expert system orsymbolic models which are a very popularapproach in the 80's decade. Their initial objectives

* Corresponding author address: Gerald Giraud,Meteo-France/Centre d'Etudes de la Neige, 1441rue de la piscine, 38406 St Martin d'Heres Cedex,France. E_mail: gera1d.giraud@meteo.fr

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are to reproduce the expert human reasoning in aparticular field. Most of them use production rulesorganised in bases (Lafeuille et aI., 1987, Giraud,1992). Recently, hybrid expert systems weredeveloped by coupling expert system and statistical(Bolognesi, 1994, Schweizer and Fohn, 1994a,Weir and Mc Clung, 1994) or neural networkapproaches (Schweizer et aI., 1994b).At the en~ of the 80's, the CEN (Centre d'Etudesde laNeige) decided to develop theSafran/Crocus/Mepra automatic suite with ananalysis meteorological model named Safran(Durand et aI, 1993), the Crocus snow model andan expert system to estimate the avalanche risksnamed Mepra (Giraud et aI, 1992). This chainsimulates the snow cover stratigraphy and theavalanche risks on many typical slopesrepresentative of the different French massifs.These slopes are characterized by differentorientations (North, East, Soith East, South, SouthWest and West), different angles and differentelevations with a vertical discretisation of 300meters. This automatic suite is an interesting toolfor regional avalanche forecasters.Recently, the CEN has developed a new tool usingonly Crocus and Mepra models on a PC for

International Snow Science Workshop (2002: Penticton, B.C.)

different applications. This tool is described in thefollowing.

2. Crocus and Mepra modelsCrocus (figure 1) is the French numerical snowmodel which calculates the energy and massevolution of snow cover. Using hourlymeteorolo 'cal data, Crocus simulates the evolution

of temperature, density, liquid water content andlayering of an initial snow pack. The originality ofthis snow model comes from its ability insimulating snow metamorphism. Snow albedo andextinction coefficient depend on the wavelengthand the surface snow type and age.

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Daily meteo and snow data

Mepra (figure 2) is an expert system for avalancherisk forecasting. This expert system deduces fromthe Crocus snow pack simulations additionalcharacteristics (shear strength, ram resistance andgrain types...). After classifying the ram andstratigraphical snow profile, this model studies thenatural and accidental mechanical stability of thesimulated snow pack and then deduces a naturalavalanche risks on a 6 levels scale (very low, low,moderate increasing, moderate decreasing, high andvery high) and an accidental avalanche risks on a 4levels scale (very low, low, moderate, high).

Figure 2 : Architecture of the Mepra expert system

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Rulebases

Snow typeShear strengthRam sonde ....

MEPRAProiIle

Nat. and Ace. mechanicalstability analysis

MeoraRisks

3. CrocusMepraPC tool

CrocusMepraPC software is a tool running on a Pc.This software has been developed in an orientedobject language (Visual C++). At the start of theCrocusMepraPC software, a toolbar appears withfile, display and window menus. To make aCrocusMepra run, the user must choose ageographical point of simulation, an initial snowprofile and meteorological conditions during thesimulation. Then a new "tool" menu and a "start"icon appear, the avalanche forecaster can runCrocus and Mepra models. Some window viewsallow him to visualise the results under differentforms.

Avalanche Forecasting

3.1 Geographical data of simulated point

For the user, the first selection is the choice of alocal simulation point using a dialog box ( figure 3).The user may choose a post in a list, create a newpost or modify the geographical characteristics andsave them. Classical geographical parameters areinputted as : orientation, altitude, slope ....and solarmasks to calculate the solar radiation at the snowsurface.

Fig 3 : Example of a dialog box to input the geographical data ofa simulated local point.

3.2 Initial profile and simulation date

~fter choosing a local point of simulation theo~ecaster must input an initial profile with it~ date

usmg another dialog box (figure 4). Each layer of

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the snow profile is described by some currentparameters like depth, density, LCW (liquid watercontent), temperature and size of grains but also bysome Crocus typical grain parameters like :dendricity, sphericity and historical. It is possible to

International Snow Science Workshop (2002: Penticton, B.C.)

load a Crocus saved snow profile or an input oldsnow profile. About the number of sinmlationdays, the limit is 10 days. The backup of Crocus

­simulated snow profiles allows us to run again themodels for a long time if necessary.

Figure 4: Dialog box of initial snow profile

3.3 Meteorological data

To make a run of Crocus and Mepra models,meteorological data at hourly time during thesimulation are necessary. These meteorologicalparameters are : air temperature, humidity, windspeed, nebulosity and rain or snow precipitations. Adialog box with window tabs (figure 5) allows theuser to input these meteorological data twice perday of simulation at 8 and 13 local time. For all theparameters except temperature, theCrocusMepraPC software makes linear

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interpolation to give hourly meteorologicalparameters to Crocus. For the air temperatureparameter, the avalanche forecaster must choosebetween a linear or algorithm interpolation usingthe "time setting" dialog box of the configurationmenu (principal toolbar). The second choiceindicates that a complex interpolation will be madeusing two sinusoidal nmctions to take into accountthe day and night evolution of the air temperature

Avalanche Forecasting-

Figure 5 : Dialog box for input of meteorological parameters

3.4 Visualisation of CrocusMepraPCresults

With the geographical characteristics of thesimulated point, the initial snow profile and thehourly meteorological temperature, the user canmake a Crocus and Mepra run using the start iconor the toolbar menu. After that, the results of the 1 .to 10 days CrocusMepra simulations are visualizeduntil 3 types of charts:

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- complete and detailed simulated snow profileswith Mepra avalanche analysis risks for 2 selectedhours of simulation (see figure 6)- graphics of snow surface temperature during thewhole simulation- graphics of hourly and complete water runoff atthe bottom of the snow pack

The user can also look at the hourly meteorologicaldata, the hourly flux calculated ly Crocus and themark of the simultion.

International Snow Science Workshop (2002: Pentiction, B.C.)

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5. References

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4, Conclusion

Some tests and validations have been made using insitu snow and avalanche data, The ISSW papernamed "In-Situ" measurements to testCrocusMepraPC tool gives more information aboutthese tests and validations (Coleou and aI, 2002).

The main limits of this tool are due to the use ofonly one dimensional models which don't allow usto take into account the spatial variability of thesnow pack at the slope scale. The Mepramechanical analysis uses only the Crocus simulatedsnow pack and doesn't take into account the snowdrift and its local effects. In the future, using theresults of the Sytron snow drift model (Durand andaI, 2002), some improvements are expected

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~ E., 1992. A numerical model to simulatew cover stratigraphy for operational avalanche

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311.Durand, Y, E. Brun, L. Merindol, G. Guyomarc'h,B. Lesaffre and E. Martin. 1993. A meteorologicalestimation ofrelevant parameters for snow models,A. Glaciol., 18, 65-71.Durand, Y, Guyomarc'h, G., Merindol, L, 2002.Research and developpements on wind transport atMeteo-France and its modeling. ISSW 29September - 4 October 2002, Penticton, BritishColumbia, Proceedings (in press)Giraud, G. 1992. MEPRA : an expert system foravalanche risk forecasting, Proceedings of theInternational snow science workshop, 4-8 Oct.1992, Breckenridge, Colorado, USA, 97-106.Lafeuille, J., P. David, J. KOnig-barde, E. Pahaut,C. Sergent and T. Granier. 1987. Intelligence

Avalanche Forecasting

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