Transcript avalanche forecasting tools

Ten years of operational numerical simulations of
snow and mountain weather conditions and
recent developments at Météo-France.
Y. Durand, G. Guyomarc'h, L. Mérindol, G. Giraud, E. Brun, E. Martin.
Météo-France, Centre d'Études de la Neige (CNRM),
1441 rue de la Piscine, F 38406 Saint Martin d'Hères.
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Introduction
The Safran/Crocus/Mepra (SCM) suite
Operational use of SCM (analysis and forecast modes)
Research use of SCM
Current developments
Conclusion
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Main Characteristics/Limitations
of the Operational SCM massifscale avalanche hazard modeling.
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-homogeneous massifs (~400 km2) with different elevations (~10),
aspects (7) and slopes(3)
-hourly simulation of a lot of complete snow profiles (T, dZ, r, LWC,
stratigraphy, stability) under the assumption that, at that scale, the
snowpack evolution is completely controlled by the atmospheric forcing
-no realistic orography but « idealized » slopes
-use only of « atmospheric » observations (no use of data concerning the
snow cover)
-use of NWP models: ARPEGE / ALADIN
-no local small scale features forcing
-crude simulation of snowdrift effects (in fresh snow crystal modification
only)
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Regional avalanche forecasting tool
Meteorological Data :
Observations,meteo model…
SAFRAN
Meteorological analysis
Analyse and forecast of
the snow pack evolution
by massif, elevation,
aspect and slope
CROCUS
Snow model
Expert system model
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MEPRA
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SAFRAN
Meteorological
NWP model
Snow and weather
observations
Classical meteo Observations
and atmospheric sounding
Analysis /6H
24H Analysis for précipitation
Hourly Interpolation for all the
parameters
Satellite
Radar (in dev.)
Hourly meteorological parameters affecting snowpack evolution
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• Meteorological
analysis for
mountain regions
• notions of massif,
altitude, aspect
• 2 days forecast
version by
adaptation of NWP
models
• OI and variationnal
methods used
•temperature and humidity
•wind velocity/ direction
•radiative fluxes
•snow and rain precipitation
•cloudiness
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SAFRAN « PRACTICAL » VERSION
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O/I scheme and Intermittent Analysis (6h)
with ARPEGE or ALADIN as guess-field
for :
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Wind (Div. + Rot.) (verticale profile + surface)
Humidity (verticale profile + surface)
Cloudiness (3 layers)
Temperature (verticale profile + surface)
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24h Rainfall Analysis based on climatology
and typical synoptic patterns.
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Variational Analysis at 1 hour step on 6h
windows.
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Several algorisms and modelling for :
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Radiations
Diurnal Variations
Vertical Snow-Rain Limits
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CROCUS
1D numerical snow model
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MEPRA
1D mechanical analysis
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Additional mechanical characteristics ,
Ram resistance profile
Shear strength profile (C)
Estimation of the applied shear stress (tn for snow, ts for skier)
Wet snow instability
Slab occurrence in superficial layers, presence of buried weak layer
S C
t
S ' C
tn ts
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Natural stability index
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Accidental stability index
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Natural avalanche risk on a 6 level scale (very low, low, moderate
increasing, moderate decreasing, high, very high)
Accidental avalanche risk on a 4 level scale (very low, low,
moderate,high)
Avalanche types (fresh dry, fresh wet, fresh mixed, surface slab,
surface wet, bottom wet)
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SAFRAN
Results (2)
24h analyzed
rainfalls
(15/11/02)
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SAFRAN
Results (3)
24h forecated rainfall
(11/01/99)
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Tests on annual
rainfall climatology
(SIM Projet).
Year 2000.
Symposium Zoning
Safran with full
observation network.
Safran with real-time
observation network.
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CROCUS
results (1)
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CROCUS results (2)
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Safran-Crocus
Validation (1)
Scatter diagrams of measured and simulated
means snow depth on 37 test sites during 4
different months over 10 winter seasons
10 years of measured (dotted) and
simulated (solid) snow depths at the
Tignes ski resort, Vanoise massif,
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2080m.
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Safran-Crocus
Validation (2)
Comparisons between observed and
numerically
simulated
snowpack
structures during the 1996-97 winter at
the ski resort of "La Plagne" (Vanoise
massif) on the snow pit location of
"Montchavin" (2100m, NE). The
different panels illustrate the weekly
observed
snow
pits
and
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corresponding computed profile. The
vertical axis (in cm) represents the
snow depth and the blue and green
curves respectively temperature and
density profiles (with two different
scales on the horizontal axis in °C and
%V). On the right side of each profile ,
the stratigraphic profile is illustrated by
color code while vertical hachures
show crusts.
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MEPRA
operational
results (1)
MEPRA : detection of an
unstable layer
In this case (1st January
1996), the model has
detected a snow structure
favourable to an avalanche
triggering by overloading
(e.g. skiers). A weak layer is
buried under 40 cm of new
snow constituting a slab
after
some
cohesion
processes.
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MEPRA
operational
results (2)
MEPRA : risk of spontaneous
(natural) avalanches due to
an unstable fresh snow
amount
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Mepra results (3)
Symbolic representation (elevation/aspects) of MEPRA natural
avalanche risks in a typical spring situation (9 March 94, 12 UTC)
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Snow and
Climate Change
Snow duration (1500 m)
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Avalanches and climate
change
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Ref.
PT
T
1,2
a
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index
index
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1,4
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Ref.
PT
T
c
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Nov. Dec. Jan. Feb. Mar. Apr. May June
All avalanches
• Rainfall +10%
Nov. Dec. Jan. Feb. Mar. Apr. May June
Melting Avalanches
Température +1.8°C
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Local avalanche forecasting tools
CrocusMepra PC
-Local simulation of
the internal state and
the mechanical stability
of the snow pack
- Analyse and forecast
mode
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SCALE DEFINITIONS
Downscaling
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Massif scale : ~ 500 km2
Local scale : ~ 1 km2
Avalanche path scale : ~ 100 m2
Time step : 1 hour
Time step : 30 min
Time step : ~ 5 min
Symbolic topography
Fine scale orography
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Snow Drift
• Slab formation, effects of snow accumulation and erosion…
• Objectives :
– Better estimation of accidental avalanche risks
– Better localisation of avalanche risks
• Experimentation in a specialized field laboratory
• Modelling:
- SAMVER : surface wind field estimation
- SYTRON1 : wind transport at the massif scale (nearly operationnal)
- SYTRON2 : wind transport at local scale
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Snow Drift
Snow depth
differences
due to snow
drift effects
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Conclusion (1)
Safran/Crocus/
Mepra chain
• Valuable avalanche forecasting tool for regional forecasters :
meteo, snow, stability and risks
• « analyse » mode with all the snow/meteorological data
• 24 and 48 H forecast with the runs of the ALADIN and ARPEGE
meteorological models and analyses by a nearest neighbour
method
• Validations :
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Meteorological (Col de Porte, Lac Blanc)
Snow depths
Snow profiles
By the avalanche forecasters
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Conclusion (2)
The SCM chain is presently running over:
24 alpine massifs
23 Pyrenean massifs
12 islandic areas
Good skiing
and thank
you for your
attention
It is operationally used by numerous forecasters.
It is still under development (snow drift, …)
It is also a research tool (climate ….)
It is used in related applications (hydrology, …)
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