modeling and forecasting the distribution of volcanic ash...
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Modeling and forecasting the distribution of volcanic ash from the Eyjafjallajökull
eruption
A. Stohl, N. I. Kristiansen, S. Eckhardt, P. Seibert, F. Prata, J. F. Burkhart, K. Tørseth
Picture courtesy: Magnús Tumi Guðmundsson
This
study is partly supported
by ESA within
the Support to Aviation
for Volcanic Ash Avoidance
(SAVAA) project
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15 April 0 UTC 16 April 0 UTC
17 April 0 UTC 18 April 0 UTC
The synoptic situation: Geopotential
@ 500 hPa
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The FLEXPART modelLagrangian
particle
dispersion
model, similar
to the one
used
at the London VAAC
Meteorological
input data:Forecasts
use
NCEP GFS data, Analyses ECMWF data
Simulation
of volcanic
ash
in 31 size
bins-
gravitational
settling
-
dry deposition-
wet
deposition
Transport of 15 million ash
particles
by mean
winds, turbulence, convection, sedimentation
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FLEXPART simulations of the eruptionSecond forecast ready: 15 April 16:00 UTC
http://transport.nilu.no/products/eyjafjallajokull
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Forecasting System
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Interactive
Tool
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The source term – the first great unknown• Total ash
emission highly
uncertain-
Assume
10% of reported
tephra
production
in modeled
size
range (0.5-290 μm)
• Time variation
of emission rate not well
known-
Take what’s
available, anecdotal
evidence
• Eruption
column
height
is variable-
Reports, satellite
data (max. height
11 km)
• Height
emission profile
unknown- 4-layer C-shape
• Ash
size
distribution
at point
of emission not well
known-
Taken
from ground
samples around
Eyjafjallajökull
but
they
are biased
towards
larger
sizes
All these
uncertainties
will
affect
the final model
result!
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Ash plume transport to Europe
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Comparison with SEVIRI ash retrievals
15 April, 10 UTC
FLEXPART total ash15 April, 9-12 UTC
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Comparison with SEVIRI ash retrievals (credit: Mike Pavolonis)
17 April, 20 UTC
FLEXPART total ash17 April, 18-21 UTC
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Comparison with SEVIRI ash retrievals (credit: Mike Pavolonis)
18 April, 4:20 UTC
FLEXPART total ash18 April, 3-6 UTC
CloudsClouds
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Comparison with AURA/OMI aerosol index (credit: AURA/OMI team)
FLEXPART total ash15 April 9-12
AURA/OMI aerosol index15 April 12 UTC
?
Increased
emission rate too
late?
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Comparison with SEVIRI ash retrievals
16 April, 6 UTC
FLEXPART total ash16 April, 3-6 UTC
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Comparison with SEVIRI ash retrievals
16 April, 18:30 UTC
FLEXPART total ash16 April, 18-21 UTC
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Good agreement with London VAAC: 16 April 00:00
Notice: qualitative
comparison;isolines
not strictly
comparable
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16 April 18:00
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17 April 12:00
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Howto
improve
the source termUse
observation
at the eruption
Site
(a priori) andUse
inverse modelling
approach
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Effect
of wind
shear4-Nov-2002 eruption of Reventador, Ecuadorare
SO2
and Ash
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Eruption
Sources x
(1..n) xa
a priory profile
Satellite observation y0
(1..m)
M
Emission sensitivity Matrix (m
n), as obtained from FLEXPART
σ
standard error of observation
Source-receptor matrix calculation with a Lagrangian particle dispersion model in backward mode, P. Seibert and A. Frank, ACP, 4, 51-63, 2004.
Inversion
Method
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Emission Profile
(Jebel, 2007)
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Challenges
of the EYJA* eruptionSource TermEruption
takes place
over a long
time periode, emissions
are constantly
added
up (started
runs every
3 hours
over 2 weeks, satellite
images available
every
15 mins -
SEVIRI)3 unknown
variables: timing, emission profile, size
distribution
TransportMainly
Ash
is emitted
–
shows many small‐scale features:
‐
ground‐bases lidar
of limited representativity, aircraft in‐situ data may
also be difficult to interpret
‐
satellite data probably best data source
‐
observations alone far from delivering information need by air traffic
authorities
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Why
is EYJA* difficult
to model
Different grainsize
–
settling
–
different transport direction
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Conclusions•
Comparison with
measurement
data encouraging, FLEXPART and operational
VAAC model
(NAME) in good qualitative agreement
•
Quantitative dispersion simulations require quantitative source term (function of height, time, particle size range) -
SO2
source terms for explosive
eruptions can be derived well with our inversion method ‐
ash
source term for
continuous eruption much more complicated, research and development needed ‐
important role for inverse modelling
of satellite data is likely, but kind and way of
usage of additional (in‐situ, ground‐based and airborne) measurements needs to
be worked out
•
Long‐lasting eruption of medium strength, emitting into the middle and upper
troposphere, have the strong impacts on air traffic as large regions are
contaminated (due to synoptic variability) and starting/landing
inhibited (due to
low elevation of ash) ‐
the cloud shape tends to be quite complicated after some
days of transport
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Thank
you
for your
attention, ESA for funding.